Highly Competitive - software industry insights

‘Big Data’, Intelligence and Multi-faceted Innovation

 

I’m using this diagram (below) in two posts – this one and one to be published shortly. Why? The impact of what this diagram is communicating is big, and affects many aspects of enterprises that want to innovate, to be competitive, to grow, to stick around for a long while. So it deserves the extra exposure.

While the use case for this example of multi-faceted innovation is Consumer Products industry, all industries have a stake here, especially as more and more technology offerings are becoming “consumerized”, and as cloud services and mobile usage for business grow. Multi-faceted innovation has great potential to transform enterprises into agile social businesses.

 

 

IBM: Enabling Multifaceted Innovation 

 

More teams in enterprises need access to more data, information, content, and many kinds of analytics to better perform their functions, to find more ways for the business to deliver what customers want, to be more competitive, more responsive in volatile economic times and in dynamic markets. Reliable, relevant information delivered at the right time impacts how strategies and goals are realized, how innovative a company can be, or even how long a company will be around. Information does no good if it languishes in silos, whether in the cloud or behind the firewall. Sophisticated and business-oriented technologies are needed to process information from diverse distributed sources, to analyze it, and then share the results for further refinement or even disputation.

The enterprise that has truly implemented multi-faceted innovation in as many aspects of its business as is appropriate is more likely to understand how important it is to tap into as many information assets as possible, whether they are ‘owned’ by the enterprise or sitting in cloud repositories for social sites. Information-driven insights are a significant aspect of multi-faceted innovation in the enterprise.

 

Business and InformationTechnology

Early in October I had the opportunity to attend an event sponsored by the Teradata Partners User Group (TDPUG). Teradata Corp. is a global vendor of software solutions for data management and governance, data warehouse capabilities, and for a wide array of analytics offerings. Obviously user group presentations usually show the positives of using vendor offering. But beyond that, the presenters usually talk fairly honestly about how they accomplished work for their companies that made a difference. The presenters are usually the hands-on people who know the ins and outs of their projects, as well as the impact on the business.

Part of my focus at the TDPUG conference – or Partners, as many call it – was attending business-oriented sessions (rather than technical deep dives) that might help with the following: 

“Big Data’ is a major topic for Teradata, and for recent acquisition Aster Data (‘big data’ analytics).  So I wanted to see how end users are able to connect highly varied and frequently complex Data to business outcomes that matter and to innovation.

Looking at processes working with data and analytics: are enterprises combining Business, Technology, Analytical, Creative, Collaborative activities to lead to good results for the business? If yes, how are they doing this? 

New directions for Teradata: how is the company changing from promoting its offerings mostly to very tech infrastructure-oriented target markets to adding strategic focus on the impacts of BI and analytics on business goals and needs – and how is Teradata connecting to roles related to the purpose of the business itself?

From the user presentations and those from Teradata: what kinds of roles are emerging, in biz and tech, that will make a difference for enterprises when it comes to data / information and analytics? 

  

A Case in Point: Strategy, Innovation and ‘Big Data’

A few sessions showed how to connect a strategic competitive intelligence core to analytical processes. A session with Vodafone (España) revealed a model for deriving real value from ‘big data’ that feeds into processes for competitive strategies that lead to innovating consumer products and business outcomes.  Instead of falling into the trap of “battling” competitors in feature-function wars, Vodafone shows that companies should be on top of what their current and desired customers want and need.  Otherwise, the risk is falling hopelessly behind customer expectations for new and important changes in the market and products that address this market.

Vodafone bills itself as ‘customer-obsessed’ and in the highly competitive mobile phone business the company has to be. The strategic Competitive Intelligence (CI) group at Vodafone works with continuous analytical processes to feed intelligence into differentiation and competitive edge – from the customer perspective. Vodafone sees a lot of opportunity in understanding distinct customer segments and from quickly providing what each segment wants and needs. Many Vodafone target markets are highly volatile, so daily data updates and analyses are de rigueur to derive “next best actions” for Vodafone to take. Decision-making results from a convergence of analytics and intelligence in key areas: sales, marketing, competitive landscape – but revolving around deeply understanding each customer segment. This Vodafone CI approach illustrates the great payoff when business data silos are eliminated to achieve real integrated intelligence, leading to effective product and business innovation.

The Vodafone session also epitomizes many of the Partners stories: when considering ‘big data’ analytic processes, the focus is not just the data itself, but what it’s used for. The data must be reliable, timely, right sources and integrations. Vodafone ‘big data’ analysis means many sources, high volume, fast intelligence leading to fast actions, and a daily reiteration of it all. Complex EDW and analytics infrastructure are aligned to business strategy and important outcomes, with a twist: the game changes constantly.

An additional layer is the continuous re-analysis of methodologies for competitive and market intelligence processes, and of the validity of selected data sources, as well as context and the inclusion of new factors. To keep the intelligence efforts relevant, the dance steps are: change, iterate, stay agile (while knowing their competitors are likely taking similar actions as happens in highly commoditized markets).

What Vodafone is accomplishing with its market and competitive intelligence core is a move to derive from an “unexpected” and innovative use of analytics the sorts of offerings that should be made available to target customers.  A new perspective on what should be the significant issues for target customers is essential to capture customer interest.  Competitive and market intelligence can also be leveraged to ensure that the customer’s perspective is maintained as a “reality check”. It’s an ongoing sense of the impact of what could be uncovered, the ramifications of what even the smallest pieces of information could mean for the company.  It ensures that business decisions and product direction are market-driven, reality-based, and actionable.

  

Information Technology Underpins Multi-faceted Innovation

When people think about what Teradata offers, most think of a very intense technology infrastructure. But Teradata and its new acquisitions, Aster and Aprimo seem to be working hard to make clear to the business users of an enterprise how that tech infrastructure connects well to what the business needs to accomplish in every part of the enterprise. These ideas were found in many of the Partners sessions:   

Every business session that I attended continued to emphasize people (roles), process, practices -- and positioned tech in context of serving the first three – very focused on real business outcomes

Real collaboration permeated the projects described in the sessions – not called out as such but well exhibited in descriptions of what was done and why – shared passion for getting real things done in effective ways, teams working cross-departmentally

Natural collaboration happens mostly in enterprises where the company ‘culture’ is open to cross-team collaboration and working to effective goals

Purposeful and constant communication across teams is very important for the success of the projects presented

Sessions drove home that data is only valuable in context – context that is comprised of many aspects of the business and how the data is to be used

It is more and more essential for people to take time to understand their data sources and the data itself, before trying to use it, before integrating it and so on >> certainly before analyzing it and using it for decision-making

The need for excellent information flow, reliable data, accurate analytics permeates every group in the enterprise, and can help these groups find more ways to innovate internal activities, as well as innovating products and services, and relationships with customers and partners

  

Multi-faceted innovation is the basis for transforming companies into innovative, dynamic and social businesses. Most companies focus innovation activities on products and services, and on finding new markets. But to survive and thrive, companies need a strategic multi-faceted commitment to innovating throughout the enterprise, how it does business, and how it interacts with customers, employees and partners. Once such a commitment is in the works, enterprises then need to understand how information technologies play significant roles for the success of multi-faceted innovation.

  

Related Links:

Information, Intelligence and Process:  Combining Forces to Better Answer Business Needs

The Ever-Expanding Importance of Analytics–True Intelligence for Business

Goals and Metrics – Measuring Customer Engagement on the Web

The incongruous worlds of “data integration” – Making data accessible for any-size companies

Custom Code or Data Integration software tools: Strategic Use of Technology for Company Competitiveness

Levels of Social – and Integration – Cut Across Enterprises 

Market Intelligence – Making Better Business Decisions at the Core of the Company

Shallow Thinking Ensures Bad Business Decisions

Software companies still fail to tap into top benefits from market & competitive intelligence programs

Connecting Data Governance to Business Outcomes That Matter

Data Management: Reaching into the Cloud

 

Disclaimer: Teradata Magazine sponsored my attendance at TDPUG, since I am doing some consulting with them.

About the author: Julie Hunt is a software industry solution strategist and analyst, providing market and competitive insights. Her 25+ years as a software professional range from the very technical side to customer-centric work in solutions consulting, sales and marketing.  Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt   For more information: Julie Hunt Consulting – Strategic Product & Market Intelligence Services    

 

Internal Disruption – No Longer Business As Usual

Tapping into periodic business model renovation to refresh competitiveness

 

Not too long ago, a tweet from Hutch Carpenter @bhc3 caught my eye:

First step in disrupting an industry: identify the "business clichés"

The tweet linked to an article by Luke Williams, known for his work on ‘disruptive thinking’ for transforming businesses through seeking the unexpected and through adopting proactive disruptive behavior and strategies. The article elaborates on what is meant by business clichés:

In other words, what are the clichés - the widespread, hackneyed beliefs that govern the way people think about and do business in a particular space… inverting or denying industry clichés can often lead to significant business breakthroughs

Williams’ notions of ‘business clichés led to a couple of tweets from me that boil down to:

…apply internally to tech co’s biz model > question assumptions, status quo, disrupt business as usual…to move to new possibilities, competitiveness, new solutions & markets

As with the Social Business, starting internally with change frequently is a better route for companies when faced with the need to disrupt current business models for survival and success purposes. Software companies are especially prone to stand on old business models well past the expiration date. And many software companies are surprised when strong competitors emerge, based on fresh business models.

  

What is a Business Model?

Business models focus software companies on target markets, customers, the solution space and, somewhat indirectly, the competitive landscape, the same matrix that underpins market intelligence. When companies seriously embrace the selection of a business model, the process introduces good and rigorous strategic thinking into decisions about company direction, as well as definition of company scope. Through the business model, the focus is holistic and interactive in terms of how the company will proceed to achieve success.

Of course there are many definitions and concepts about what comprises a business model. A lot of MBA school, entrepreneurial, and VC hours have been spent on not only deciding what is the optimal business model for a particular undertaking but on the strategies to carry out its intentions.

  

The shortest definition that I’ve come across is in a post by Tim Berry: A business model is a description of how your business intends to operate and make money. Berry then goes to the next level:   

But innovative business models go beyond this simple formula to create customer loyalty, make value in unusual ways, and define new products or services that people didn’t know they needed.  

This dovetails somewhat with a business model definition put together by IBM:

• What value is delivered to customers: Customer segments, the value proposition, the specific “job to be done,” what is sold and how it is sold

• How revenue is generated: the pricing model and forms of monetization

• How the company positions itself in the industry: the company’s role and relationships across the value chain

• How the value is delivered: Key internal resources and processes as well as external partnerships.

There is lots of disagreement, lots of vague notions regarding whether business models matter or not.  Some consider the business model almost a sacred object, carved in stone. More and more, many see each iteration of the business model as disposable. A new class of thinking sees the business model not as an end but an ever-evolving means to success as a company.

 

Articulating New Direction - Most Companies Not Very Good At Doing This

Intriguing idea: the disposable business model. But how many companies pull off such an approach?

From my experience in the software industry, not many. Particularly bad at changing direction are mid-sized software vendors that are publicly traded. While being a smaller company would suggest agility for change, often these companies are ham-strung by boards of directors who seem to want growth without risk. There is no growth without risk for most companies. One piece of advice to mid-sized software vendors is to never go public and thus retain a healthy ability to reinvent the company without the inertia of boards of directors and Wall Street expectations. Another piece of advice: learn to embrace risk: that is, the good kind that can lead to growth and new success.

But no matter the size of the company, many software vendors usually wait too long before assessing the health of the current business model and even then, are slow to articulate change, even slower to act effectively. As a result, core markets increasingly stagnate, management still tries to work with the old way of doing things, and fails to work genuinely on a new business model, or as Williams advises, to identify and then deny the business clichés that are dragging down the company.

In 2008 Mark W. Johnson, Clayton M. Christensen, and Henning Kagermann published the article “Reinventing Your Business Model” in the Harvard Business Review, an article that went on to receive second-place honors for the 2008 McKinsey Award. The article culminates research into the difficulties many companies have with pulling off success through business model innovation. The authors contend that these companies have such poor understanding of the current business model (really disturbing! but explains a lot…) that they can’t relate the current model to new opportunities, nor can they be confident about ejecting the current model for something new.

(Clay Christensen) also underscores the fatal flaw that managers make when trying to reinvent their business in the face of a disruptive competitor. Their solution is often to leverage what the company already has in place at marginal cost rather build an entirely new business model with heavy investment.

If you are trying to create a new business model because the world is changing, then you don’t want to leverage what is already in place. An entrant doesn’t have anything to leverage, so just creates what needs to be created.

 

When It’s Time For Reinvention

A 2005 survey by the Economist Intelligence Unit reported that over 50% of executives believe business model innovation will become even more important for success than product or service innovation. A 2008 IBM survey of corporate CEOs echoed these results. Nearly all of the CEOs polled reported the need to adapt their business models; more than two-thirds said that extensive changes were required. And in these tough economic times, some CEOs are already looking to business model innovation to address permanent shifts in their market landscapes.

 

Insanity: doing the same thing over and over and expecting different results 

-- Albert Einstein

  

Of course, there’s no point to changing the business model if the company isn’t innovating its software offerings, which must come about by “disrupting business as usual” internal to the company. Not all product innovation demands a reinvention of the business model. Perhaps the salient question is: how does this new innovation impact the proposition articulated for customer value? Companies that find success with business model reinvention also possess clear understanding of their customers and the value to those customers that comes from innovations.

Identify When A New Model May Be Needed:

An opportunity to...           

• Address needs of large groups who find existing solutions too expensive or complicated
• Capitalize on new technology, or leverage existing technologies in new markets
• Bring a job-to-be-done focus where it doesn’t exist

 A need to . . .

• Fend off low-end disruptors.
• Respond to shifts in competition

 

To determine whether a firm should seek to reinvent its business model, Johnson, Christensen and Kagermann advise these steps:

• Articulate what makes your existing model successful. For example, what customer problem does it solve? How does it make money for your firm?
• Watch for signals that your model needs changing, such as tough new competitors on the horizon.
• Decide whether reinventing your model is worth the effort. The answer is yes only if the new model changes the industry or market. 

So the new proposition for staying competitive may be that many companies will need to adopt the strategy of continuous business model reinvention. But to do this, tremendous internal change will have to happen, particularly around the management of the company. Reinvention, new directions, continuous competitiveness -- all are only possible in companies that embrace change and innovation in the corporate cultural DNA.

 

             
                              Source: IBM CEO study – Capitalizing on Complexity

 

Comprehensive Market Intelligence is Key to Business Model Disruption

A lot of what can make a software company more competitive – and can contribute to innovation of business models, markets and products – comes from well-executed Market Intelligence activities and processes. Excellent Market Intelligence is essential if business model reinvention will be an on-going initiative. Understanding customers, markets, channels and competitors is based on better information to create advantage in new and unique ways:

• New opportunities – identify new trends that will matter to target markets and customers; how to get there before the competition (whenever possible)
• Early warning of industry, market and/or competitor changes – take advantage of opportunities and leverage/deal with threats and risk, and always look over your shoulder…
• Enhanced customer interaction – understand customer POV, goals, needs, strategic direction
• Stronger target market selection & positioning – research, validate go-to-market and positioning; locate under-served markets for target customers and solution space; guide how to articulate positioning well for customers, analysts, industry
• Strategic view of competitive landscape – figure out true differentiation, figure out where competitors are not operating; understand the issues that matter to customers and the solutions they seek from competitors

 

 

Reinvention: Brand Equity / Brand Perception

I want to open up the question of how business model reinvention impacts Brand, both in terms of brand equity (value and general recognition built from the former business model) and brand perception (how current and potential customers – plus media, competitors, analysts, etc. – view the company). In the not-so-distant past, it had been considered near suicide to make business model changes that could negatively impact Brand. But in the digital age, when information is quickly disseminated through endless media, most people are easily educated about changes in a company. The Internet itself is all about constant change, and many have grown up in that environment.

I’m not going to explore the Brand aspect in this article but it is an issue that must be considered when reinventing business models and enacting innovation that impacts customer perception and receptivity to the company’s offerings.

  

Smaller Companies With Disruptive Genes – Better At Business Model Reinvention?

>> JackBe – Customer-Driven Disruption

JackBe started off as an Ajax tools vendor in 2001. After a while the company began targeting enterprises with a mashup platform that connects to all sorts of data sources. Responding to what JackBe customers wanted, the next development was to provide capabilities for ad hoc data integration mashups by end users.

Recently JackBe has been calling itself ‘the Real-Time Intelligence Company’, specializing in situational awareness, and is promoting the idea that the company may have a new way to provide business intelligence for enterprise end users. Real-Time intelligence for JackBe first of all means self-service BI, extrapolating its mashup services for end users. Real-Time also means fast, easy access to existing data sources, without concern about the freshness of the data. Essentially, the JackBe approach supports instant decision-making in certain scenarios.

A significant challenge entails the validation of data sources and value of the resulting mash-ups: do the end users understand what they are doing and are they intelligently combining the appropriate data? Is the intelligence that is pulled together relevant and accurate, and how do end users know or test the intelligence to provide validation?

By stepping into the larger arena of BI, JackBe now has invited in scrutiny from a well-established solution space. However, traditional BI is not without its problems and has suffered low adoption and success rates over time. It may be that JackBe is pioneering a new approach that could make a significant change to how BI is practiced or even what constitutes “business intelligence”.

JackBe has found itself moving into a new business model, seemingly a case where business model reinvention continues to be customer-driven, and where a company listens well to its customers and acts on their needs and wishes, to achieve competitive positioning and success. But with the new business model comes new challenges to ensure the validity and accuracy of its product directions.

  

>> NewsGator – One Business Model Dies Out, Another Adopted to Thrive

Starting in 2003, Newsgator focused on developing RSS usage for information and content consumption.  A business model shift occurred when NewsGator changed from a consumer focus to targeting enterprises. Even though NewsGator still provides RSS, access is now free.

In 2007, NewsGator reinvented its business model by launching Social Sites, community / collaboration software that also provides tight integration with Microsoft SharePoint. NewsGator was already a SharePoint partner for its RSS capabilities, so its business model shift pivoted on a strategic, and rather significant, partnership already in place. NewsGator acquired Tomoye community software in 2010, mainly to enter new markets. Tomoye also had the SharePoint connection.

The move to a communities / collaboration platform that extends SharePoint has proven to be successful to date. The new business model includes a deep commitment to Microsoft and SharePoint – and active cultivation of an ecosystem of Microsoft partners around “making SharePoint social”. Social Sites is built directly on the SharePoint platform, is SharePoint cloud certified, supports multiple versions of SharePoint, including mobile and Office 365.

NewsGator has selected a niche for its social solutions in that it is dedicated to complementing the SharePoint platform and to making the experience of using Social Sites with SharePoint a seamless and smooth experience for end users. With this business model, NewsGator success is highly dependent on continued SharePoint success. The up side is that Microsoft makes available an extensive ecosystem that can greatly benefit NewsGator.

One aspect of business model reinvention for NewsGator tracks back to the impact of reinvention on Brand. Does the company name still make sense, shifting from RSS/aggregation services to social media platform? Or does the brand recognition of NewsGator’s name trump any confusion about what the company now does? Frankly, considering that a good many software company names are obscure, this really shouldn’t be an obstacle for NewsGator, particularly with such a targeted solution in conjunction with SharePoint.

  

>> Stone Bond – From Services to Software Vendor

There are many cases where professional services providers for IT solutions will either productize services work into a software offering or purposefully create new software solutions that eventually evolve into a packaged software business for the services company. A key change in business model comes when the company must decide if it is to be a dedicated software vendor or a services company – or even, perhaps, the company decides to split into two organizations.

Stone Bond’s consulting services began in 1993, providing IT solutions for the worldwide oil and gas industry. Among the services was data modeling projects, working with oil company engineers as end users. Many in the oil and gas industry have long understood that their data is a very valuable asset.

In 2002 Stone Bond Technologies launched a software solution called Enterprise Enabler for data and business integration projects. Enterprise Enabler presents as a single environment for EAI and ETL capabilities and is somewhat geared towards end users / business users through out-of-the-box “codeless” data integration capabilities. Stone Bond has developed several technologies such as AppComs (for connectivity) to innovate how integration projects are created and executed. BPM and workflow based on SOA utilize end-to-end shared metadata.

While Stone Bond still targets the oil and gas industry, and obviously has a great deal of expertise for that industry, the company has already taken Enterprise Enabler into other markets, such as financial services and government. The solution also straddles target customers by offering a solution that can appeal to business users and/or IT teams. Enterprise Enabler may be blazing a trail for bringing together IT and business to better execute data integration projects as collaborative partners.

The company is now working on showcasing Enterprise Enabler as a software product independent of the original consulting business, with work going into raising brand awareness. Enterprise Enabler already has a solid customer base, but also seems like a “best-kept secret” in the data integration vendor space. In some ways, Stone Bond has an interesting clean slate when it comes to marketing to and educating the world on what this solution has to offer.

 

Related Links

Market Intelligence – Making Better Business Decisions at the Core of the Company

Software companies still fail to tap into top benefits from market and competitive intelligence programs

Provocation-based Market Intelligence in a Market-Driven world

Shallow Thinking Ensures Bad Business Decisions

B2B WEM / WCM Software Vendors Targeting Mid-Market customers: stay where you are!  

 

About the author: Julie Hunt is an accomplished software industry analyst, providing strategic market and competitive insights. Her 20+ years as a software professional range from the very technical side to customer-centric work in solutions consulting, sales and marketing.  Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt   For more information: Julie Hunt Consulting – Strategic Product & Market Intelligence Services

 

Disclaimer: Julie Hunt is not affiliated with any of the vendors in this article.

 

The Ever-Expanding Importance of Analytics – True Intelligence for Business

“Intelligence” is a word much bandied about in enterprises. Frankly few enterprises use it properly to denote what constitutes authentic intelligence.

"Intelligence is nothing if not an institutionalized black market in perishable commodities"

Master spy novelist John LeCarré

While the above notion is intended to refer to information gathered by spies regarding enemies, this sort of thinking has colored how enterprises view intelligence: the secret information that will solve all problems and kill all enemies. It doesn’t matter if you’re talking business intelligence or market / competitive intelligence. The apparent allure of the military and spy industries for enterprises has badly skewed how many companies view intelligence.

The kind of intelligence that truly benefits enterprises derives from classic definitions of the word: learning, understanding, applying knowledge and experience to new situations to make better decisions. For both business intelligence and market/competitive intelligence, the frequent catchphrase is “making better business decisions”. Both involve data, analysis, recommendations. Both can have strategic and tactical applications. Both benefit from qualitative as well as quantitative dimensions. And both should strive for authentic INTELLIGENCE, not just resultant collections of information.

Business Intelligence methodologies and tech solutions have been used to generate actionable views of a company, frequently rooted in business operations. Until recently, BI outputs have been primarily reports – some might say too many non-contextual reports, many of which may be trivial, pointless, or worse, misleading. The BI world includes analytics, data mining, text mining and predictive analytics.

And sometimes BI is considered to be ‘competitive intelligence’, hence my references to market intelligence. Market/competitive intelligence and business intelligence should be complementary, but are not the same thing. In my view, a certain amount of BI output contributes ‘intelligent data’ for market intelligence initiatives. Overall, market intelligence gleans from many ‘data’ sources from many disparate sources inside and outside the firewall, both qualitative and quantitative, while filtered by specific strategic contexts. Until recently, BI has mostly derived from practices and technology that address structured data and business processes inside the firewall. BI will now have to include unstructured or content sources in analytics, to add in missing subtleties, context, and insight that cannot be pulled from structured data sources.

Analytics Everywhere

In addition to overt BI-style analytics, many other analytics solutions have been proliferating to help make better business decisions. Web analytics were silo’d for a while as relevant only to website usages. But web analytics now have many forms and have become very sophisticated. Data captured by web analytics is now important to many teams across the enterprise and is now becoming more integrated into other “business intelligence” endeavors.

With fast-growing social media applications, SM analytics are now emerging – again the data generated is essential and must be integrated into the overall intelligence base of the enterprise. Content analytics have become even more important as unstructured content proliferates from many sources.

These seemingly diverse analytics cannot be confined to individual silos in enterprises. “Intelligence for the Business” that results from all analytics is needed at LOB / department levels, as well as at the über-enterprise level. And mid-market enterprises need such business intelligence capabilities as well. So all kinds of analytic tools need to become more accessible to many roles and organizational segments that have not necessarily been targets of such solutions before.

Unfortunately, keeping pace with the enormous proliferation of data, and even with the various analytical outputs, is overwhelming many enterprises. More integration between what began as silos of analytics must now happen. Enterprises have to get better at the behind-the-scenes / get-your-hands-dirty work that is essential to make realistic and effective use of all the data (structured and unstructured) pouring in from so many sources. The Semantic Web will likely contribute overall to the integration of structured and unstructured data to add to intelligence relevance.

Predictive Analytics – The Bold New LOB Tool

Considered a subset of BI, but also present in other categories of analytics solutions, predictive analytics may become much more in demand than traditional BI solutions, especially with the new directions of innovative predictive analytics solution vendors.

Eric Segal of Information Management on predictive analytics – citing a marketing use case:

Predictive analytics is data mining technology that uses your customer data to build a predictive model specialized for your business. …The real trick is to find the best predictive model.

…a careful combination of predictors perform better customer prediction by considering multiple aspects of your customers and their behaviors. Predictive analytics finds the right way to combine predictors by building a model optimized according to your customer data.

Predictive analytics builds models automatically, but the overall business process to direct and integrate predictive analytics is by no means automatic - it truly needs your marketing expertise.

Predictive analytics can be part of “traditional” BI offerings – it’s also part of the web analytics world. Baynote provides ‘Adaptive Web’ solutions that include analytics, personalization and social search for customer-focused relevance on websites, to help optimize engagement and retention. Baynote’s Collective Intelligence Platform provides companies with predictive analytics based on the implicit patterns of customers visiting their websites. Omniture, WebTrends and other web analytics solutions also provide capabilities for predictive analytics.

Content Analytics, Content Intelligence

Enterprises have been challenged for years on the content intelligence front – it has been very difficult and very messy to extract meaning (and thus retaining context) from unstructured content to be used as “data”. The amount of enterprise content is enormous, with geometric expansion in play. For enterprises that publish content on the web, content analytics also offer the means to better connect with target markets and customers:

"Content analytics" can be seen as business intelligence (BI) for/from content, as text (rather than number) crunching that generates insights to improve business outcomes. The two practices, content analytics and BI, certainly share motivations. If you don't analyze your content/data, you may be missing opportunities and running risks.

For content publishers, analytics drives better targeted content delivery, expanded audiences, and secondary uses and new distribution channels. These outcomes add up to profit. On the flip side, they are matched by reduced risk and cost avoidance given possibilities for more complete, more accurate compliance screening, e-discovery, and storage management.

Analytics also boosts value for users. Semantic search, faceted navigation, and content annotation/enrichment create findability and improve user experience and value for users. They also let users treat content like data. Call the goal "content intelligence," enabled by "smart content."

Seth Grimes on Content Analytics

 

“Intelligence” Hits The Wall

Stephen Few’s graphic for “BI Has Hit the Wall” is quite expressive of where BI – and all analytics - need to head to deliver evolving value to enterprises. Stephen Few is a leading expert in creating effective data visualizations that communicate real intelligence and don’t just function as “eye candy”:

Contained in these early definitions was the seed of an inspiring vision that caused people like me to imagine a better world, but the business intelligence industry has done little to help us achieve the vision of the people who coined the term. When Thornton May was interviewing people for his book “The New Know”, he asked a prominent venture capitalist known for his 360-degree view of the technology industry what he thought of when he heard the phrase business intelligence. His response was “big software, little analysis.”

For information to be useful, we must explore it, analyze it, communicate it, and monitor it, but the BI industry’s attempts to support these activities with few exceptions have been tragically comical. The technology-centric, engineering-oriented perspective and skill set that has allowed the industry to build an information infrastructure is not what’s needed to support data sense-making. To use the data that we’ve amassed, a human-centric, design-oriented perspective and skill set is needed.

New World Focus on BI and Predictive Analytics

Some of the significant changes to analytics solutions relate to how final artifacts are “formatted”. There has been a growing transition from traditional report formats to interactive visualization tools, and to collaborative processes that enhance the final artifacts. More companies want BI to help with current and future needs and goals, rather than measuring the past. And these companies should be inviting in more and more individuals (via collaboration) to help refine the accuracy and contributions of analytics outputs. Newer on-demand BI / analytics solutions are providing “right now” intelligence, though still these are still works-in-progress, for the most part.

A number of articles lately have made the point that BI initiatives have not been highly successful for many customers, while making another important point: that “failure” actually is part of the BI refinement cycle. But for costly enterprise-style BI solutions, “failure” can be quite expensive. Gerry Brown of Bloor comments:

However, there is little doubt that the number of BI users overall is increasing. With low-cost operators such as QlikTech, Tableau, LogiXML, Pentaho and Jaspersoft you get an awful lot of BI software for $25,000. Conversely, most enterprise BI vendors don't traditionally get out of bed for deals of less than $50,000. Low cost (or 'free') BI software encourages trial and experimentation with little risk, and this is what most enterprises prefer. After all, BI project 'failures' are common.

Referring again to the graphic for “BI Has Hit the Wall”, Stephen Few sees that “the traditional BI software vendors and most of the industry’s thought leaders are stuck on the left side of the wall” – while the future of BI will come from more non-traditional BI solutions:

The software vendors that are providing effective data sense-making solutions—those that make it possible to work in the realm of analytics on the right side of the wall—have come from outside the traditional BI marketplace. Vendors like Tableau, TIBCO Spotfire, Panopticon, Advisor Solutions, and SAS tend to either be spin-offs of university research or companies that have ventured into the BI marketplace from a long history of work in statistics.

In a very interesting and thought-provoking Gartner Magic Quadrant for BI platforms, the analysts see significant changes in the solutions sought by enterprises:

…there is significant, if not euphoric, satisfaction with, and accelerated interest in, pure-play BI platforms. This is particularly true for smaller, innovative vendors filling needs left unmet by the larger vendors. To understand this paradox, it is necessary to consider a number of factors that are driving the BI platform buying decision today.

Other vendors to watch for new ways to perform and use BI / analytics include Lyzasoft, Predixion Software and GoodData. Lyzasoft and Predixion recently became partners for cloud to cloud analytics-as-a-service. GoodData provides BI PaaS to help speed up solution deployments.

BI SaaS adoption, while very low today, will grow steadily as maturing BI SaaS solutions are delivered in private and public clouds and in on-premises and off-premises configurations by trusted vendors. …innovative, pure-play vendors offering highly interactive and graphical user interfaces built on alternative in-memory architectures to address their unmet ease-of-use and rapid deployment needs. The perceived benefit is so compelling that business users are making this choice, despite the risk of creating fragmented silos of applications and tools.

Business users in particular showed a growing impatience with the time to deploy and complexity of traditional enterprise tools, which led to a rise in departmental buying of alternatives.

Collaboration and the Human Element

One newer area of interest for BI / analytics solutions is the inclusion of collaborative activities to add contextual and qualitative layers to the output of BI processes. To achieve authentic intelligence, contextual / qualitative layers can provide strong basis to test, fine tune and filter the artifacts of analytics. Analytics can benefit greatly from human filters that bring experience, knowledge, creative thinking. Context has a big role here: context for sources, context for outcomes, context for usage with other data points to achieve the best Intelligence for “making better business decisions”.

Collaboration is far more than distributing and sharing documents. It is interactive, inclusive, cross-enterprise. If collaboration is to be part of analytics, then iterative collaborative processes should be established throughout analytics cycles. Collaboration for analytics means bringing in disparate people to test assumptions, validity of data sources, accuracy and relevance of the outputs. These additional participants should provide a wealth of experience, complementary concepts and other essential data and perspectives. Having to prove the relevance and accuracy of analytics results to sympathetic as well as less sympathetic individuals should strengthen BI / analytic processes and projects.

The possibilities for new applications of analytics increase with collaboration. Inviting in many-to-many interactions also opens up processes to new ideas from participants. Gartner found that social venues and collaboration help to track and capture outcomes of the decisions made based on BI / analytics:

Gartner's user surveys show that improved decision making is the key driver of BI purchases. However, most BI deployments emphasize information delivery and analysis to support fact-based decision making, but fail to link BI content with the decision itself, the decision outcome, or with the related collaboration and other decision inputs. This makes it impossible to capture decision-making best practices. Solutions are emerging that tie BI with social software and collaborative tools for higher-quality, more transparent decisions that will increase the value derived from BI applications.

Vendors embracing collaboration as an essential part of BI / analytics include Lyzasoft, Predixion and Tibco Spotfire. Keep in mind that these vendors are all in early stages of building in collaboration as a significant aspect of their analytics solutions.

Analytics Aren’t Always Fun and Games

While there are very interesting analytics solutions that are “friendly” to business users, it is essential that safeguards are in place to ensure that business users understand what they are doing with analytic models and whether the resulting “intelligence” artifacts are correct, meaningful and useful. Collaboration with others who know the data, understand analytics, visualize the big picture, and so on, is one safeguard to ensure reliable analytics outcomes and correct usages.

In a particular enterprise, do enough people know what to do with analytics, both to start processes in meaningful ways and to audit outcomes to validate accuracy and relevance? Are users chasing the right problems or questions, providing the right data sources, including enough pieces? Do they have the understanding to work in a “big-picture” sense? Yes, analytics vendors should build in methods for validation, testing, guidance, but is that enough? Bob Warfield addresses this concern:

Few enterprises have the right analytical talent.

I was musing not long ago with VC and fellow EI Evangelos Simoudis that very few people actually know how to ask questions in a way that solves problems. It is something of a Sherlock Holmes conundrum. All the data is available. It is shatteringly obvious once someone connects the dots. Yet, very few know how to step across the stones that peek above the raging torrent of data to get to the other side where the answer lies without falling in and getting wet.

“You see Watson, but you do not observe.”

Beyond the traditional users of BI / analytics, there is an additional “challenge” to vendors to reach potential users who “need predictive analytics but don’t know it”. The challenge comes in two parts: first to find them and connect meaningfully with them; and then to provide guidance for every step of using the analytics solution to ensure proper outcomes. To connect with these “new” analytics users, vendors have to help them understand why they need analytics and how to use it. Self-serve training modules must be available for using the solution but also for understanding what analytics mean to the user’s role, industry and business needs. Detailed templates and best practices organized by industry scenarios are also important for success. It will be interesting to see how successful various vendors are for empowering such non-traditional users.

The Elephant in the Room: Reliable Structured Data

Although I’m not addressing data warehousing in this article, I do want to point out the need for basing any data-driven intelligence / analytics processes on reliable data. While it’s the right direction to provide analytics tools that work well for business users and increase ease-of-implementation and ease-of-use, diligence must be exercised to guarantee that data sources fed into analytic processes are trustworthy. Otherwise GIGO.

Teams comprised of IT and business must collaborate to create and maintain excellent processes for data profiling, data cleansing / quality, and data integration. The business users know how source data is used and the context for analytic processes. IT is the partner to help with the data profiling, data quality and integration steps. Data profiling tools can be used by business users to audit data sources, test for errors and/or for the lack of the right data, and to understand different data sources.

"Intelligence is nothing if not an institutionalized black market in perishable commodities"

A lot of data and content that matter for better “Intelligence for the Business” come with a short shelf life of significance. The new direction for many analytics solutions should bring this information more quickly into intelligence processes. When enterprises succeed in achieving richly integrated knowledge and context, authentic INTELLIGENCE is likely to result for “making better business decisions”.

Related Links

Market Intelligence – Making Better Business Decisions at the Core of the Company

Shallow Thinking Ensures Bad Business Decisions

Software companies still fail to tap into top benefits from market & competitive intelligence programs

Levels of Social – and Integration – Cut Across Enterprises

The incongruous worlds of “data integration” – Making data accessible for any-size companies

Custom Code or Data Integration software tools: Strategic Use of Technology for Company Competitiveness

Content Marketing Strategy for B2B Software Vendors: Starring the ‘New’ White Paper

Disclaimer: Julie Hunt is not affiliated with any of the vendors in this article.

About the author: Julie Hunt is an accomplished software industry analyst, providing strategic market and competitive insights. Her 20+ years as a software professional range from the very technical side to customer-centric work in solutions consulting, sales and marketing. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategic Product & Market Intelligence Services

I have a confession to make: I am a Hybrid

B2B Software Vendors: Hybrid Roles for Business Technology

 

  

 

 

Like many other companies, software companies have allowed silos of work activity and responsibility to proliferate with adverse effects. There are now increased efforts to improve collaboration and cross-team project work to bring best efforts into play for company competitiveness. The ever-increasing presence of social collaboration practices and social media applications are driving changes to corporate collaboration cultures.

  

 

The demands of innovation, meeting customer needs, and rapidly changing solution markets are challenging software companies to work much more quickly and collaboratively than ever before. SW companies need to innovate: job roles, how work is done, better collaboration practices. Software companies are showing increasing need for “hybrid” roles even though few software companies are actively encouraging an evolution in how work roles are defined. 

  

 

Hybrid roles are intersection points for cross-team expertise, collaboration and communication. People in hybrid roles understand many different perspectives both internal and external to the company. The hybrid professional works to integrate multiple perspectives in work being done with multiple teams. Hybrids have real potential for broadly connecting the dots in new ways, to help company innovation and competitiveness. For software companies, what hybrids can do somewhat parallels the “good kind” of integration and convergence of solution spaces, and even of the companies themselves, into new entities.

  

 

To be able to communicate across many teams, hybrid roles must be “multi-lingual”: techie talk, customer speak, product management/product marketing lingo, as well as the lingua franca of reality checks. Creative thinking, new directions, new ways of looking  at the business of the company not only contribute to the positive direction of the company but also are effective for catching problems with current initiatives and strategies.

  

 

 

  

Different Hybrid Roles Are Popping Up in Many Companies

Common denominators for hybrid roles in different disciplines and industries seem to include: specific deep knowledge in multiple subject matter areas, technology astuteness, the understanding of business needs that cross traditional boundaries, belief in collaboration, even the use of social capabilities to support work processes and better communication.  Hybrid roles are frequently focused on crossing silos to achieve better results and to see bigger pictures.

 

  

CIO Hybrids

With the need to better align IT responsibilities with corporate business, many CIO positions are evolving into hybrid roles. There is strong strategic reasoning behind CIOs taking on cross-team and cross-functional positions. By placing CIOs in hybrid roles, they have more power and visibility to be able to improve enterprise-wide processes, to have real impact on business goals, and to better tie technology to the business. In the companies that have migrated CIOs to hybrid roles, the CIOs have more opportunity and punch to influence how technology and the business can work together for the overall good of the company.

  

  

 

Theses hybrid roles are very demanding for both the CIO and the IT group. As with all other technology-related hybrid roles, there is a risky side, particularly with the CIO stepping into areas not traditionally the usual tech turf.  But for the CIO to better support the business of the business, she/he must have real participation in business and overall strategic decisions for the enterprise.

  

 

Indeed, CIOs who have taken on additional business are better positioned to deliver improved processes and business results. "I am both the customer and provider of a solution. There are people on my team that are using technology to generate revenue, and there are people on my team who are delivering technology"

 

 

  

Marketing Technology Hybrid

Scott Brinker published an extensive and well-crafted piece on the rise of the marketing technologist, which describes yet another hybrid role. He thoroughly considers the future of “technology-powered marketing” where “Marketing must take ownership of the technology in its domain”. I highly recommend reading the entire article. 

 

 

  

Some of Scott’s observations on the marketing technologist hybrid:

As marketers, you're already responsible for the outcomes based on such technology. The accountability so widely promoted in digital marketing has you in the hot seat for results. It's only sensible that you should have full control over the means and mechanisms to deliver those results.

 

 

  

You must be the driver of marketing technology, not merely a concerned passenger. But if you don't have technical depth, who can help you navigate? …I propose a new role in the marketing department: a marketing CTO or chief marketing technologist. The mission of the marketing CTO is to provide that technology navigation.

 

 

  

I believe that digital marketing is more like product development than IT because it is:

· More front-office than back-office

· Experienced directly by customers

· An engine for new revenue

· Integral to the brand

· Visible in competitive positioning

· A creative endeavor

 

 

  

Financial expert / Business Analyst / Software Developer

Rummaging around the ‘net I found this recent job posting for “Business Analyst - Financial Accounting - Developer Role”

So if you are an accounting/finance professional who also has a technology background, apply!
* Background in accounting and general knowledge of GAAP
* Excellent communications skills
* Bachelors Degree in Accounting, Finance or related
* 5+ years working in technology as an (systems) analyst or developer

 

  

  

So What Makes Me a Hybrid?

Being a hybrid is risky business – I know from personal and professional experience. But it is also extremely rewarding, where the unexpected is just around the corner. My particular hybrid perspective draws on down-in-the-trenches experience in the technology, business, and people-oriented aspects of creating, marketing and selling software. My other hybrid bits include product/solution strategy, market and competitive intelligence, GTM strategy.  

  

 

A hybrid perspective comes in very handy for constructing relevant strategic market and competitive intelligence, recommendations for company competitiveness and innovations, and understanding whether a company’s software technology can map to new customer solution scenarios. I can bring a perspective of understanding how all the pieces fit and inter-relate, when working with different teams.  Such a perspective also helps with “seeing outside oneself” to visualize how a company is positioned in the larger worlds of solution spaces, markets and the overall software industry.

  

 

 

   
    

  

Overcoming Problems - Achieving Wider Acceptance

For hybrid roles to become part of strategic staffing in software companies, cultural and organizational change will have to take place, particularly in upper management and HR groups. Management-engendered cultural change should lead to company teams better accepting the value of hybrid professionals. Collaborative thinking in software companies will need to stretch out of traditional silos. Also needed is a much better understanding of what hybrids can accomplish for business and project goals, and the value of such accomplishments to the company.

  

Another impediment to accepting and understanding hybrid roles is the issue of job titles.  Most existing titles don’t adequately express what a hybrid really embodies and is capable of doing.  When trying to “identify” an employee as a hybrid, titles often deteriorate into dreadful, overly long hyphenated messes, or worse, opaque “vanity” titles. Along with an evolution in the types of positions and work done for software companies, there is a need to create more meaningful titles for many positions.

  

 

HR department gatekeepers likely will not understand these hybrid roles and their value to software companies: hybrids don’t fit the pre-built HR system job definitions that harken from the late ‘90’s. Upper management and HR must update approaches to filling key positions by enabling inclusion of new breeds of professionals that companies need to attain more innovative thinking and change how work is done.

 

  

In writing about “Social Is A Hybrid” Rich Nadworny - @rnadworny – makes these important points:

I've spoken to a few hybrids who, while providing invaluable services to their companies, lost their jobs when new bosses couldn't understand their function or value.

 

 

  

The challenge for most businesses is that people don't operate as hybrids. They operate within silos, with clear role definitions and even clearer budgets.

 

 

  

The bigger question for businesses today is whether they accept hybrid structures and if they support the growth of hybrid individuals

 

  

  

Hybrid Roles Matter for Software Companies to be Competitive

It may well be time for software companies to give way to evolution for how work is done, where work is done, and how workers connect with one another to achieve business goals. Hybrid roles have the potential to facilitate some of the evolution:

· Help show the way to redefine key roles – time to abandon traditional roles to achieve better results and truly tap into experience and knowledge needed across multiple teams

· Provide new thinking to assist with eliminating more silos that inhibit better cross-team collaboration, big picture perspective and faster results

· Improve cross-team communication by seeing the big picture from multiple POVs and speaking multiple “languages”

· Fuel much-needed innovation and new solution direction – connecting the unexpected dots and knowing why the connection matters

· Hybrids are more likely to feel at home with social media, social CRM and collaboration practices, and usually make excellent advocates for the use of social in software companies

 

  

The increasing proliferation of social capabilities and practices in many companies will lead to more hybrids, particularly as companies transition to becoming “social businesses”. Social business will require new roles to bridge gaps, improve communication, weigh the relevance of new ideas, and better understand customer perspectives. However, a hybrid role is not a position of omniscience – continuous and healthy cross-team collaboration (including customer relationships) is extremely important for best results.

 

  

Companies lose out when they do not recognize, employ and nurture hybrid professionals who will contribute a great deal to the business. Considering the lack of acceptance and recognition by most software companies, it’s little wonder that so many hybrids become independent consultants. Unfortunately for these companies, these hybrids take with them the broad and deep team-spanning IP that so many software companies seriously need.

  

 

  

Related posts:

 Shallow Thinking Ensures Bad Business Decisions

 Software companies still fail to tap into top benefits from market and competitive intelligence programs

 B2B Social CRM for Software Vendors and the Lifecycle of Customer Experience

  

 

About the author: Julie Hunt is an accomplished market intelligence analyst, providing strategic market and competitive insights for the software industry. Her 20+ years as a software professional range from the very technical side  to customer-centric work in solutions consulting, sales and marketing.  Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt   For more information: Julie Hunt Consulting – Market & Competitive Intelligence Services  

 

Customer Buying Criteria: Applying customer and competitive intelligence to selling tools leads to real external benefits -- and strategic internal benefits

B2B Software vendors

 

Many software solutions will prevail if customer-centric, market-driven thinking permeates the company’s product development planning and execution, and go-to-market strategy.  Understanding customer buying criteria is essential in: solution markets crowded with many vendors, highly commoditized software markets, and/or markets for complex software solutions. Determining and using customer buying criteria will help teams in the company understand where each solution stands relative to the competitive landscape and the appeal of each solution as the right solution from the customer POV.

 

A tool configured as a Customer Buying Criteria (CBC) matrix can very helpful to sales teams to work effectively with customers-as-buyers. The CBC matrix can bring a lot of clarity to mapping a software solution to the wants and needs of a particular customer. This is a tool that relies not only on extensive customer and competitive intelligence, but on the cumulative wisdom and experience of multiple teams in the software company.

 

 

Cross-team Collaboration to Build the Best Sales Tools

Market and competitive intelligence for software companies is at its best when the results of analysis are used in applications that help and support many internal teams: sales, products teams, marketing, management. As a corollary, a lot of the best tools for sales teams require cross-team collaboration. This sort of collaborative effort is essential to create tools that are smart and thorough in every way possible. Contributing teams include:

· MI/CI for competitive landscape, market analysis, target customer analysis

· Product marketing / management for evaluations of software vendors own solution and understanding of customers, markets and competitors

· Sales, professional services, partners – feedback from customer engagements

· Reviews of the resulting tool by all for determining realistic values for ratings and relevancy of criteria and capabilities

 

Tools developed by cross-team efforts frequently reciprocate “paid back” value to collaboration participants by providing a new “benchmark” to use for strategic and tactical self-review and analysis for improvement. Most software companies are short on people and time, even when the economy is good.  As such, it is important to choose projects that yield both strategic and tactical benefits to many teams, and that have the depth to generate spin-off projects and tools.

 

 

Conceptual Overview of Customer Buying Criteria Sales Tool

The Customer Buying Criteria tool greatly enhances sales efforts by tapping into the understanding of what customers want.  The CBC tool dovetails well with consultative selling where the sales team (and the software company) becomes a “trusted advisor” helping the customer-as-buyer successfully solve business problems. With the CBC tool, sales teams have real talking points for the buying criteria that matter to customers, to be able to speak the same language. Instead of communicating with a customer by blathering on about product features/functions or “7 reasons to buy my product”, much more meaningful exchanges take place where the customer is driving the conversation based on what she/he wants to buy.

 

If a software vendor does not know what its customers want, the vendor will not be able to convince customers to buy its offerings. It’s not about “my product is better than competitor X” – it’s about “my product will give you what you need to be successful with your needs”. Most mid-market and enterprise software solution markets are more and more driven by expectations that are pre-defined by customers.

 

A clearly defined context for the software solution is essential for a customer buying criteria tool to be effective. The tool will comprise a single solution that the company is offering, that it does well and for which there is a strong market. Context also means that using the CBC tool well is highly dependent on fully understanding customer requirements for each individual sales opportunity (no one-size-fits-all).

Setting context is everything: 

· One single clearly defined solution per tool

· Identifies target market

· Why the customer should care

· Attributes that matter to the customer

· Spell out the product solution’s particular positioning in the larger solution market (ex.: web experience management for large global enterprise websites – external-facing sites – customer-engaging – within the high end WCM market)

 

How does a software vendor determine the customer buying criteria for a particular solution?  It’s all about what target customers want from the solution – in their words, from their POV. The key customer buying criteria (categories and capabilities) are developed based on industry expertise and customer engagements, and are not “traditional” feature comparisons. Sources for determining criteria include:

· Customer interviews and surveys

· Customer segmented market research

· Sales and partner feedback

· Industry writers and analysts

· Information from companies you would like to have as customers, potentially gained through partners (resellers, SIs, solution providers, etc.)

· Market and competitive intelligence analysis – particularly to validate future market directions and competitive landscape intentions

 

 

Practical Overview of Customer Buying Criteria Tool

The overall CBC tool comprises a superset of all relevant customer buying criteria in order of importance, based on what was determined through the research and analysis process.  Under each criterion are multiple solution capabilities that customers understand and need for meeting project requirement. These capabilities are not feature/function lists from the product POV, but higher level and expressed in customer terms.

 

Before the sales team uses the CBC tool for sales engagements, an excellent and thorough discovery with each customer must be conducted to understand the specific criteria that come into play (what matters, what doesn’t). If the sales team doesn’t understand what each customer-as-buyer needs, then the tool is of little use.

 

The CBC tool can never be left with customers. First of all, a lot of the software company’s competitive information exists in the tool.  Second, leaving this sort of tool does not adhere to consultative interaction and does not help the conversation with the customer. (More on these points: Software companies still fail to tap into top benefits from market and competitive intelligence programs)

 

 

Recommendations for building a CBC Tool

· Consider using Excel to take advantage of customizable viewing options

· Entries for key customer buying criteria

o    Several high level criteria categories - each with multiple capabilities

o    Criteria in order of customer priority

o    Criteria mapped to sales cycle phases

· Criteria aligned to primary & secondary target customer roles for discussing each buying criteria category

o    Many B2B customers-as-buyers are composites of multiple roles

o    Different phases of “sales cycle” will map to one or more roles, such as BU, IT

· For ease of viewing / using:

o    Collapsible / Expandable groups of rows customize view

o    Can hide unneeded competitor columns

o    URL links in cells, to navigate to supporting content in company’s internal archives

· Competitors: from left to right = most important to least important

· Can include more than one relevant current release of your company’s particular solution 

· Competitor versions should be most current – provide release #s

· Ratings are assigned based on an assessment of the support for each capability provided by each vendor (your software company and competitors)

o    Ratings will have a qualitative nature and could be:

§  Green – above average (better, best)

§  Yellow – average (adequate, so-so)

§  Red – below average (not good, missing)

· Data for deciding ratings for your solution come from all products teams, and participating sales and professional services

· Data for deciding each competitor rating comes primarily from third-party sources (links in cells) – preferably multiple third-party sources, and will reflect input from all other teams through review processes

 

There is definitely a qualitative aspect to the ratings in the CBC tool, but it is mitigated by the extensive research and analysis done for understanding and evaluating the competitive landscape. Further reviews by company teams and partners will bring the “wisdom of the crowd” (and the “wisdom of the gut”) to evaluating the overall accuracy of the ratings and of the resulting “big picture”. The company’s own ratings should follow an approach where the contributing teams are the harshest critics for how well the company’s solution delivers on capabilities for the customer buying criteria.

 

Fine-tuning on a continuous basis must happen to keep the tool fresh and responsive to customer and market changes, as well as new product/solution releases.  Maintenance of the tool will cover changes and corrections contributed by the company’s teams, feedback from customers and partners, and industry evolution. The tool is structured to enable ease of updating and publishing new versions quickly.

 

Setting up the Customer Buying Criteria tool as a superset of all relevant criteria makes it possible to generate subsets as smaller, focused versions. These permutations can be provided for niche/industry focus, particular customer subsets or solution scenarios, or views of particular competitors, whether for selling or for internal purposes.

 

 

Sample CBC Tool

Benefits of using Customer Buying Criteria Tools

 

Successful outcomes to engaging customers-as-buyers require all teams collaborating in many different ways – constructing a well-made CBC tool provides the collective expertise of multiple teams.  For sales teams, the tool is a source of many permutations of talking points. New hires for sales will find this tool especially helpful to ramp up more quickly.  The CBC tool aligns sales cycle strategy with the software offering, relative to individual customer requirements, needs, and desires. For each sales opportunity, the sales team can scan across the matrix of the company’s offering compared to competitors to get a quick sense of where strengths, weaknesses – and serious trouble – come into play in the context of each customer’s requirements. In a sense, the tool provides a huge and very useful Reality Check for every sales opportunity, even to the point of using the tool as part of the qualifying process:  is this opportunity really worth pursuing, is the deck stacked against us, what gaps will have to be filled to work well for the customer? 

 

Customer benefits from the CBC tool are indirect (since the tool is not shared with customer) but still important:

· Better basis for sales to talk with customer – conversation moves along more realistically while engaging customer with true customer needs and concerns, and in language of the customer

· Customer can decide earlier in sales cycle if solution really is a fit – from the start, the conversation has been from customer POV and relevant to customer needs, requirements and desires

· Better identify what criteria really matter for project, and which criteria are optional

· Customer can see that the software company thoroughly understands the solution space from the customer POV

 

For the products teams, including product marketing, the CBC tool can be a reality check on how well the company provides relevant customer-centric, market-driven solutions. Looking at capabilities / rankings of the company compared to competitors:

· Allows the teams to step outside the “day to day” and really look strategically at the offering and how it stacks up in the competitive landscape

· Evaluates how the company is / isn’t meeting customer expectations and requirements

· Provides close scrutiny of differentiation and whether the company is stuck in too much “me too” development

· Taps the tool as a metric for the software solution and for its competitiveness

· May lead to new thinking for creating new solutions,  better differentiation, more creative approach to solving customer problems, increased competitiveness, and better quality for the solution

 

Upper management now has a tool to help see and better understand the big picture, especially for complex software solutions selling into crowded markets.  Hopefully, the CBC tool will enable better dialogues between the executive and the products teams, working from common basis.

 

 

 

About the author: Julie Hunt is an accomplished market intelligence analyst, providing strategic market and competitive insights for the software industry. Her 20+ years as a software professional range from the very technical side  to customer-centric work in solutions consulting, sales and marketing.  Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt   For more information: Julie Hunt Consulting – Market & Competitive Intelligence Services  

Software companies still fail to tap into top benefits from market and competitive intelligence programs

 

 

MI Programs for Software Industry Distinct from MI Programs for Other Industries

Implementations of market and competitive intelligence for software companies are quite different from the corresponding programs in other industries.  For one thing, the software industry is very fast-paced and does not have the luxury of lengthy timeframes for building complex market intelligence processes of the sort that are usually promoted for other industries.  MI for the software industry must be agile and frequent. It requires not only 360° experience in software from the technical to sales & marketing, but also requires a distinctive creative streak and the ability to view things “differently”. 

 

Through a program of deep research and analysis, filtered by subject matter expertise, a top notch Market Intelligence program can bring significant value to a software company. Essential attributes include qualitative and intuitive insight, and a fearlessness to look beyond the obvious to connect the unexpected dots. A channeled passion for software technology drives many right-on-target projects and initiatives.

 

To build innovative competitive recommendations, market intelligence has to question other people’s assumptions about the industry, even if those people are prominent in the company. The incumbent company consensus view should not be taken at face value by the market intelligence professional.  Instead, the MI program should examine such strategic assumptions, and then should be able to provide the data to support either the incumbent view or to delineate a different direction, or even a hybrid alternative.

 

MI makes a significant difference for the competitiveness of software companies: 

· New opportunities – identify new trends that will matter to target markets and customers; how to get there before the competition (whenever possible)

· Early warning of industry and/or competitor changes – take advantage of opportunities and leverage/deal with threats and risk

· Enhanced customer interaction – understand customer POV, goals, needs, strategic direction

· Stronger target market selection & positioning – research, validate go-to-market and positioning; locate under-served markets for target customers and solution space; guide how to articulate positioning well for customers, analysts, industry

· Strategic view of competitive landscape – figure out true differentiation, figure out where competitors are not operating; understand the issues that matter to customers and the solutions they seek from competitors

· Comprehensive development of MI deliverables – publish to multiple parties; consolidate cross-functional needs to produce more; ensure top quality and relevance

 

Where Software Companies Take Wrong Turns with MI/CI Programs

Many software companies continue to think of market and competitive intelligence as tactical methods to attack competitors, to convince a customer not to buy from a competitor, instead of: developing their own strategic solution offerings, building strategic relationships with customers, and understanding how to help customers really solve their problems and support their business initiatives with reliable solutions.

 

Competitive Intelligence programs are frequently tightly aligned with Sales groups. Sales Management often demands that MI teams focus on “feature-function” product comparisons with competitors, harkening back to old school sales techniques that focused only on “my product is better than the other guy’s product”. Today’s software target markets are for the most part commoditized, so feature/function comparisons don’t win business.  Commoditization also makes impossible the old school notions of “silver bullets” and “setting landmines” for competitors.  Even years ago, such tactics were usually a waste of time for many customer engagements.

 

However feature-function analyses do have value when they belong to product management groups, and are done to understand how a company’s solutions measure up against competitor offerings, and how all solutions measure up to meet expectations of target markets and customers.  These analyses are to be used internally by the products teams to improve their company solutions and go-to-market strategies.  To maintain credibility and thoroughness, such feature-function analyses are best done by third-party firms. 

  

Sales teams can be tempted to use feature-function comparisons to competitors as “customer leave-behinds”.  Feature-function analyses should never be handed out to customers for a number of reasons: 

· Introducing details that have nothing to do with customer needs and therefore detouring focused conversations with customers

· “One-size-fits-all” customer “leave-behinds” are weak tools when it comes to engaging customers

· Aiding competitors in winning the business by pointing out what they do better

· Opening the door for potential litigation from either the customer or competitors

 

Market and competitive intelligence is best used by sales teams to understand proactive strategic solution positioning that is stronger and more likely to connect to the customer’s mindset and desires. It can be used to prepare solid refutations of competitor objections.  The inclusion of competitive intelligence in a sales plan should be early in the strategic planning.

 

Tactical demands can overwhelm opportunities for delivering strategic insight.

Market Intelligence teams in many software companies walk a tightrope between the overwhelming number of daily requests (many of which have to be fulfilled within 24-48 hours), and more strategic research/analysis. Market Intelligence teams deserve more time to deliver the “wow factor” to corporate strategies derived from deeper insight about the intelligence that affects the business. Most MI professionals constantly “battle” to extract themselves from “today” research, to be able to dig deeper into future trends and customer desires, to help predict where the company should seed innovation and find new markets.

 

Additionally, MI/CI teams in many software companies frequently consist of a single person who is required to support several teams with disparate needs. The result is that a valuable strategic resource is spread too thin.  On a daily basis there are too many “fire-fighting” requests instead of large blocks of time dedicated to strategic and market-driven work.  Granted that a certain number of tactical projects are needed to bring reality into the MI program; but very quickly the program must shift a majority of effort to the strategic, especially if there is only one MI professional.

 

Projects for Market Intelligence programs should be handled like good software requirements management:  weigh each request and corresponding benefit against the strategic goals of the company, the likelihood of success, the sustainability of each project for long-term gains.  Give the MI team the authority to say “no”, and don’t put the team in the position of having to accept every tactical request.   

 

More Effective Positioning of Market Intelligence

For a software company to derive full value from a market and competitive intelligence program, it has to start with the executive level making a strong commitment to the program.  Many software industry MI programs fall short because the executive level does not position the MI program as a key stakeholder in strategic decision-making processes, nor does the executive include the MI professional in key meetings. 

 

It would be greatly beneficial if executives would direct more attention to the MI work accomplished for strategic decision-making, even when the recommendations make them uncomfortable.  This is particularly relevant in the software industry where far too many companies set “me too” goals, chasing what competitors have already done, instead of finding the more innovative path.

 

The power of a market intelligence professional lies in advanced expertise, both for subject matter and for effective implementations of market and competitive intelligence programs.  Impactful insight and perspective that bring competitive advantage to an enterprise are best achieved when the MI program approximates an “entrepreneurial” center, where innovative thinking sets the tone.  Frequently, each problem or situation requiring market intelligence is different from previous problems and usually requires a whole new solution and form of deliverable to be effective, relevant and timely.

 

While directly benefiting multiple teams in different ways, all strategic work done by the Market Intelligence team will ultimately benefit sales teams and successful deals:

· Product Management – Enable market-driven solution decisions, identify opportunities and threats, better understand target markets and customers,

· Product Marketing – Contribute to positioning, review messaging in marketing materials, generation of competitive studies, overcoming objections, make sure the actual technology maps to planned solutions

· Senior Management -  Trends, strategic views of competitors, decision-making support

· Sales – Competitiveness as a strategic process rather than a reactive one-off

 

Intrinsic Value of Market Intelligence for the Software Industry

Market Intelligence for the software industry has a unique value that might even be called Solutions Intelligence.  Market Intelligence has a significant role for go-to-market plans and sales models.  For software companies, Market Intelligence is an important conduit for deep understanding of market-driven and customer-centric orientations that are essential for competitive advantage and sustainability.

 

What it all boils down to is this: will your software company be able to efficiently, quickly and completely understand market opportunities or threats, and then react effectively to create maximum business impact?  Then empower your market intelligence professional to do the right kind of timely and strategic work that makes a big difference.

 

 

 

About the author: Julie Hunt is an accomplished market intelligence analyst, providing strategic market and competitive insights for the software industry. Her 20+ years as a software professional range from the very technical side  to customer-centric work in solutions consulting, sales and marketing.  Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt   For more information: Julie Hunt Consulting – Market & Competitive Intelligence Services  

Shallow Thinking Ensures Bad Business Decisions

 

 

The term “strategy” is tossed around a lot in companies – and too many companies seem to constantly change “strategy” in an oxymoronic fashion.  To derive a strategy of intrinsic value, it’s more realistic to consider key strategy not as a single “vision” but as a composite of what makes the enterprise tick.  Since many larger enterprises are aggregates of business units and cross-functional teams, core strategy must reflect the constant feedback from the organizational composite. This sort of continuous fine-tuning process requires significant in-depth probing, discussion and decision-making, to yield superior results.

 

Unfortunately, deep thought seems to be falling by the wayside in many companies.  Companies that claim strategic interest in innovation and forward thinking, actually tend to discourage deep probing of the usually complex subjects that matter to company success.  More and more senior managers have tendencies to actually discourage creative thinking in other employees, while repeating corporate-speak mantras: “think outside the box”, “push the envelope”, “provide thought leadership”. Instead, some executives look for external answers in hackneyed recycled material from the latest “business management gurus”. These executives seem to prefer the glib over the substantive.

 

Many managers do not give enough thought to the kind of information that they need.  Truly important competitive issues are often things that management has not yet imagined. Corporations have many teams in place who already understand quite a bit about the issues through hard-earned knowledge, analytical longevity and direct experience.  Instead of trusting these teams to provide valuable insight, many managers want over-simplified, poorly substantiated “info-bullets” that are fast to digest, built not from reality but from desired outcomes. If corporate management strategies could indeed be reduced to a few simple bullets, then every company would easily be successful.

 

Shallow thinking impacts the validity of the core strategy of the enterprise. Shallow thinking impacts the kind of research that is done – and therefore impacts the quality and depth of information and analysis available to managers, upon which they base decisions.  And shallow thinking affects executive management willingness to listen to others. By thinking superficially about topics and issues that are actually difficult and complex, company managers can oversimplify goals and pursue answers for the wrong questions. 

 

Among the teams that could have direct impact on corporate strategic thinking are market/competitive intelligence teams. The optimal relationship between the executive and market intelligence teams would be direct collaboration on a regular basis, though few enterprises institute such an approach.

 

Market Intelligence programs should be looking into what can be “known” about the future, particularly to understand potential impact, both good and bad, on corporate strategy, at multiple levels.  An essential function of MI is rigorous analysis of many kinds of “data” to be able to consolidate pertinent recommendations for strategic thinking. Unfortunately, executive management frequently falls short when it comes to listening to and considering the recommendations of the MI team. Often complex data has been analyzed by MI team, so simplistic recommendations do not necessarily result. 

 

The best MI deliverables should clearly convey what the analysis and recommendations mean in context, and how to use them. Presenting the “big picture” is important, but it is also essential to show the connection to the real details and facts, in order to provide proof and sustain credibility. Company leadership duties include setting the core vision and framing an agenda to accomplish it, but leadership also needs market intelligence to gain clear focus on the salient details that connect strategy to the realities of target markets, customers, the competitive landscape, as well as the solution space.

 

 

 

About the author: Julie Hunt is an accomplished market intelligence analyst, providing strategic market and competitive insights for the software industry. Her 20+ years as a software professional range from the very technical side  to customer-centric work in solutions consulting, sales and marketing.  Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt   For more information: Julie Hunt Consulting – Market & Competitive Intelligence Services  

Provocation-based Market Intelligence in a Market-Driven world

 

These days most software solutions align with highly commoditized markets in a relatively short time. So it is essential for software vendors to attract customers, and eventual sales, through true ROI and through differentiation other than feature/function sets.  Market Intelligence programs, in collaboration with product marketing, are important sources of comprehensive research, analysis and recommendations for providing the elements of a software solution that can set it apart, from the customer perspective.  Given the rapid pace of the software industry, market intelligence programs would benefit from a provocation-based methodology, as described by Geoffrey Moore et al.

 

Commoditized markets are buyers markets, where price tends to rule.  So customers may well consider “lesser” solutions that are cheaper and usually easier to implement and use, rather than stick to incumbent solutions that have become bloated with too many features. Market intelligence programs should focus on analyzing these alternative solutions to understand the value perceived by customers, and the fresher approach these software solutions are leveraging. 

 

Instead of falling into the trap of battling traditional competitors in feature-function wars, software companies should be learning from newer entrants into their target markets in order to maintain competitive edge.  Otherwise, the risk is falling hopelessly behind customer expectations for new and important changes in the market and the software solutions that address this market.

 

The notion of provocation-based market intelligence derives from an “unexpected” and innovative POV for what solutions should be offered to target customers.  Generally provocative issues will be strategic, will matter more to customer management teams (preferably C-level), should be somewhat surprising but relate to known issues for the customer, and inspire a desire to find a solution.  Through strategic Market Intelligence, the development of a customer-oriented “provocation” derives from aligning capabilities of solutions to the strategic business needs of customers – in a real and legitimate way. The analysis performed by market intelligence programs will also reveal the gaps that must be filled to provide the whole solution, again from the customer perspective.

 

Provocation-based market intelligence helps software companies see their competitive challenges from a new perspective that focuses on the specific pain points of customers where true urgency can be invoked, in order to attach greater importance on the solutions for such pain points offered by the software company.  The software vendor has to make it crystal clear to customers that the problems must be handled, and that doing nothing is not at all possible because too much is at stake for the health of the customers’ companies (or alternatively, customers will lose competitive advantage if they do not solve these problems, preferably by using the software company’s solution.

 

A new angle of what should be significant issues for target customers is essential to capture customer interest.  Provocation-based market intelligence can be extremely valuable in looking at a problem in “unusual” ways to identify innovative views of the problem as well as unexpected approaches to the solution.  Market intelligence can also be leveraged to ensure that the customer’s perspective is maintained as a “reality check”.

 

To truly connect to and convince customers, domain expertise is essential. The “conversation” with customers must show that the software company really understands the issue/problem and the risk of not resolving it.  Benefit must be shown clearly.  A decent plan needs to be articulated.  Data, real-world examples, next steps, all are important to gain customer confidence and buy-in. Domain expertise will come in part from Market Intelligence but will also come from other teams in the software company or even consulting partners.

 

Employing provocation-based Market Intelligence should help software companies avoid the “me too” trap of emulating the other vendors in the competitive landscape.  It will jumpstart original thinking and better focus on target customer needs. 

Collaborative work in the software company is necessary to devise the most fruitful provocations that are aligned with solutions that realistically can be provided by the software company.  The collaborative attitude should also extend to target customer interactions to make sure the customer finds the provocation of importance, to fine-tune the solution approach, and then function as a true solution partner for customer success.

 

 

About the author: Julie Hunt is an accomplished market intelligence analyst, providing strategic market and competitive insights for the software industry. Her 20+ years as a software professional range from the very technical side  to customer-centric work in solutions consulting, sales and marketing.  Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt   For more information: Julie Hunt Consulting – Market & Competitive Intelligence Services  

Market Intelligence – Making Better Business Decisions at the Core of the Company

 

Market Intelligence is essential for creating strong product strategy and for fine-tuning that strategy as industries, markets, customers, the product space, and competitors evolve over time.  And “time” in the software industry is measured in nanoseconds.  Fast-changing industries, such as software technology, require more attention on MI:  more monitoring and quicker management action.  Core decisions for businesses must be based on reasonable understanding of significant and likely future events – what the potential impact could be, good and bad. Market intelligence is the dynamic means for uncovering essential future-pointing intelligence as early as possible, averting “nasty surprises” and discovering new opportunities before the competition.

 

Market Intelligence provides the strongest value when it is aligned with product strategy groups or even corporate strategy.  It is positioned as a virtual hub for the entire company, interacting with all groups both for gathering information and for sharing intelligence and actionable recommendations.  The MI professional for software companies must be very technical and really understand the technology basis for the core competency of the company.  A market intelligence program consists of continuous processes, monitoring and analysis regarding a particular matrix of: products, customers, markets, and competitors.  The intelligence gathered is also weighed relative to the business and goals of the company.  Once analyses are completed, the market intelligence professional generates many sorts of collateral to assist the company, primarily with strategic decisions, but also with tactical needs.  Collateral includes executive alerts, competitive selling guidelines, actionable recommendations for product direction both for near and not-so-near futures. The process of market intelligence is iterative and responsive to changes in the above-mentioned matrix during the lifecycle of software products.

 

Market Intelligence differs from business research (and traditional business intelligence) through context, a certain mindset held while the research phase is done.  The market intelligence professional always has in mind the company, its business and product space, the industry and markets, and the drivers behind the need for intelligence.  It’s an ongoing sense of the impact of what could be uncovered, the ramifications of what even the smallest pieces of information could mean for the company.  It ensures that business decisions and product direction are market-driven, reality-based, and actionable.

 

The power of a market intelligence professional lies in advanced expertise, both for subject areas and for effective implementations of market and competitive intelligence programs.  Impactful insight and perspective that truly bring competitive advantage to an enterprise are best achieved when the MI professional maintains an entrepreneurial and creative approach.  Frequently, each problem or situation requiring market intelligence is different from previous problems and usually requires a whole new solution and form of deliverable to be effective, relevant and timely.

 

 

About the author: Julie Hunt is an accomplished market intelligence analyst, providing strategic market and competitive insights for the software industry. Her 20+ years as a software professional range from the very technical side  to customer-centric work in solutions consulting, sales and marketing.  Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt   For more information: Julie Hunt Consulting – Market Intelligence Services