Highly Competitive - software industry insights

Master Data Management Rebooted

 

Part 1 of a multi-part series on the "New Age of Master Data Management"

 

The 'New Age' of Master Data Management

It's about time that master data management (MDM) enjoyed a 'new age'. The creation and use of master data for business purposes has always been a good idea. The goal has been to make sense of all data that touches the organization: clean it up, add context, enrich it, and put it to work strategically as well as operationally.

Unfortunately, MDM has been plagued with certain problems from the very start. This stems mostly from the fact that MDM lands hard on some of the messiest aspects of an organization: data silos, unconnected systems and processes, management turf wars, and organizational roadblocks to disparate people working effectively together for common purpose.

 

Why Does Master Data Matter?

As the importance, value and sheer volume of data assets grow, so does the critical need for trustworthy, up-to-date information that is ready-to-go for any purpose. MDM processes consolidate data from numerous sources in meaningful ways. Master data also provides context and reveals data relationships for sources like big data that often exist as fragments without useful referential connections.

Master data has a large and growing role in areas that matter to organizations: strong brand presence, multichannel customer interactions, right-fit content and information, and highly variable buying journeys.

Analytics, particularly of the real-time variety, produce more realistic and trustworthy results when utilizing master data. Master data is often a key part of predictive analytics in support of: supply chain processes; personalization for improved customer experiences; logistics; operational optimization; and safety and preventive procedures.

A core element of MDM is data quality. Improved data quality impacts endless aspects of the business for reasons that should be obvious. But all too often, business management fails to comprehend how much poor data quality impacts profitability, productivity and even perception of the brand. Real world incidents that have been repeated at far too many organizations include:

• Inconsistent data of poor quality has led to extensive quantities of items in warehouses to "disappear" from systems records, never to be sold or consumed by the business. This can amount to millions of dollars of losses.
• Contradictory and confusing product lists and catalogs that deter purchases by customers and make sales staff look stupid – again with no purchases resulting.
• Costly pricing errors that persist undetected over time can have breath-taking negative impact on the bottom line.

 

Roadblocks, Detours, Dead Ends

Over time traditional approaches for MDM implementations have faltered for several reasons, many of which echo the failures of traditional ERP installations:

• Implementations take too long and cost too much.
• Project scope is often much too large.
• Business and IT teams are poorly coordinated for achieving the desired end state.
• Results fail to meet important business needs and / or show value in an obvious and timely fashion.
• Traditional approaches lag in keeping up with new technologies.
• Solutions have delayed including new data sources like the many varieties of big data.

A continuing obstacle is the lack of involvement of upper management with such important activities. If organizations want to tap into more data that is trustworthy and business-ready, it requires buy-in from upper management on down. Such buy-in is shown through clear commitments, upper management champions, and real data strategies – basically understanding the high value of data and what it takes to achieve it.

 

The Reality of MDM: People and Politics

What many people get wrong about MDM is thinking that it's all about the technology. In reality, it's much more about people, processes, and (unfortunately) politics. The people and politics of the organization can throw up significant obstacles to successful MDM programs. This is more likely to happen in organizations where upper level management has failed to provide its leadership and involvement in MDM implementations.

Silos permeate organizations from top to bottom, and not just in terms of software systems or digital assets. Collaboration between people is often limited. Internal politics can bring on secrecy or "turf wars" when it comes to the ownership of data and business processes. Resistance to change, lack of trust, desires to "hoard" data and information all come into play. Orchestration and collaboration of business and technical teams have always been critical to MDM success, but can be derailed by internal silos and politics.

Of course, technology provides an important means to achieve MDM implementations. But many vital activities aren't technical. For MDM and data governance to be successful, distinct changes must take place in organizations to eliminate the many silos that prevent the generation of reliable and up-to-date master data.

Not surprisingly, when things go wrong, organizations want to blame MDM technologies for the failures, instead of facing up to what really ails the organization. However, traditional MDM solutions have had significant limitations and often don't do much to help with the "people problem".

 

Wanted: Improved Approaches

A classic approach to MDM, the "bottom up" method, has not worked well simply because unsynchronized teams are trudging separate long roads to achieve the "desired end state" and often don't ever get there. It's easy to imagine the many ways that this method can be derailed. Instead, businesses benefit most from MDM approaches that work the way the business and its employees need to function to achieve real goals and objectives.

One of the most important changes to MDM approaches has organically grown out of the fact that much of MDM and data governance revolves around business use cases and business users. So it's gratifying to see more overtly business-defined approaches that not only delineate the approach but are enabling changes to the technologies that support them. These business-defined approaches reflect the complex, sophisticated needs of many organizations:

• Working from the desired end state and / or from the requirements of complex business problems to create master data management processes.
• Choosing contextual and analytic MDM solutions over traditional MDM tools that can handle new approaches for multi-dimensional and complex hierarchical data, including social and commercial graphs that underlie business use cases such as customer-responsive interactions across digital channels.
• Utilizing new MDM platforms that simplify the development of industry-focused business applications that take advantage of master data to solve business problems.
• Transforming model-driven approaches to be more flexible and agile in order to work with existing business processes as the starting point (instead of creating new processes), to deliver business value more quickly. IT and business teams can then transition to optimizing various processes for additional value.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

In a real world example, a pharmaceuticals company has utilized a new MDM solution to uncover significant information that improves the success of promoting drugs to individual healthcare organizations. Such information includes:

• Which insurance companies or payers accepted by the healthcare organization actually cover the drugs
• And for those payers, which insurance plans provide coverage
• What contracts for the pharmaceuticals company are already in place
• What other sales teams in the same company are already promoting to the healthcare organization
• Other important influence and decision-making factors that derive from complex hierarchies and networks of relationships

Running through such an analysis based on master data before approaching a healthcare organization helps the sales team determine if any business opportunities exist, and reveals better ways to approach contacts in the organization.

 

Master Data Management Rebooted

In the next five posts, I'll present and analyze what is changing for master data management approaches and solutions, including new technologies, and the evolutionary involvement of business roles in MDM and data governance.

One of the final aspects that I'll explore is this: is it time to quit calling it "master data management" and devise a name that better fits MDM Rebooted?

 

Image Source: hbr.org

 

About the author: Julie is an independent consultant and industry analyst for B2B software solutions, providing services to vendors to improve strategies for customers and target markets, products and solutions, and future direction. Julie has expertise in several solution spaces including: data integration and data quality; analytics and BI; business process, workflow and collaboration; digital marketing, WCM and social media; and the pivotal importance of user and customer experiences. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective

 

Cloud Integration: One Platform, Diverse Users

 

Final article of a six-part series on the essential interwoven nature of Business and Modern Data Integration

 

When we're talking about diverse categories of users for data management software solutions such as data and application integration, it's essential to understand the perspective of each group of users and their needs and abilities, in order to develop the most suitable user interface and the right capabilities for each category.

The future of cloud integration platforms may belong to vendors that step up to truly understand diverse users and then deliver what they require to be successful.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Today cloud-based integration platforms are opening access to different categories of users including less-technical business users. Business users have begun to assume more hands-on use of integration capabilities to run pre-built integrations, profile datasets, perform data prep functions, and even create basic integrations through wizards and pre-configured components. This is a very important means to an equally important end: taking advantage of the availability of more data to help these users do their jobs better, to benefit the organization.

Vendors for cloud integration platforms are also beginning to recognize and support diverse technical users. There can be quite a bit of difference between a technically-adept line-of-business developer who lacks deep experience for creating integration processes, and a developer who is a data integration expert and likely tackling complex integration scenarios. Each category of developer requires the right user interface and capabilities to create, run and manage integrations, in order to accomplish work requirements and support business objectives.

I recently talked with a vendor that is focused on providing a single cloud integration platform for diverse user categories. The vendor is building out a framework of ten different categories of technical and business roles with a clear view to how the platform would be used by each category. This exploration of how different users make use of integration capabilities should help this vendor streamline and perfect what it takes for different users to work well not only on their own but with other user categories when needed. This requires the platform to guide each user category to the appropriate capabilities, including a role-responsive or adaptive UI.

Another cloud integration vendor is developing a vision for multiple categories of users with schematics for how they may continuously interact during several aspects of typical integration phases. For each category of user, the appropriate platform capabilities are pinpointed along the integration phase continuum. The vendor wants to expand the solution platform to shepherd and enable this symbiotic approach to business and IT working together for more effective integration processes.

When we're talking about different categories of users for data management functions, it's essential to understand the perspective of each group of users and their needs and abilities, in order to develop the most suitable user interface and the right capabilities for each category. In that sense, it takes an outside-in perspective, working from what different users need from data management functions like data integration, and how they are comfortable working. This is a very different approach for most integration vendors – the focus has long been solely on the technology (which obviously is still important). However usability from the user perspective has been a critical topic for software vendors for quite a while.

 

The Technologies Behind "Simple" User Interfaces

A cloud integration platform that is designed to support a variety of user access options clearly requires the development of sophisticated technologies that essentially make the complex seem simple to the user. Different categories of users often require variable versions of the same user interface that are streamlined for ease of use, and that provide access to role-appropriate capabilities.

As such, the integration solution can be distinctly shaped by the variety of user roles that are provided access to the platform.

Often the work done to enable less-technical users can also benefit UIs and capabilities for more technically-adept users, providing faster paths to creating integrations. More technical users can take advantage of pre-built integrations, shared services and components that require little or no coding, just as less technical users can. For those who need it, most cloud integration platforms include the ability to customize and extend pre-built integrations through coding and other methods.

Obviously to keep less technical users on the straight-and-narrow, monitoring and management by centralized IT teams behind the scenes are essential elements. Setting up the right balance of management and freedom for business users will take some hard work, but will pay off as certain integration activities can be handed off to business users. This is another area of business-IT collaboration that requires IT to enable business users to work with integration processes, not to prohibit them.

Cloud integration platforms provide other technologies to guide all categories of users to more quickly and confidently build, test and run integration processes. Such technologies include role-aware, interactive "tooltip" constructs that pop up in the UI in response to an action or choice. The influence of mobile apps and digital games can be seen in the better "tip systems".

UI-based guidance techniques include "crowd-sourced" recommendations that are derived from the analysis of all integrations in multi-tenant platforms. Analysis processes look at how similar integrations have handled certain steps or are constructed overall, elucidated by the context of what the user is trying to accomplish. Equally helpful, interactive assistance tools focus on quickly resolving errors by showing the most likely solutions in order of relevance.

The UI has become an essential element for usability in cloud integration platforms and obviously has inspired a great deal of innovation to benefit all users.

 

The User Experience of Data

In a sense, diverse business roles and different kinds of developers have both been "underserved" by integration solutions. All too often non-IT users are lumped into the single blob of "business users" which is pretty useless for understanding much about who those business users are or how they want to – or even should – use integration solutions. And developers are usually seen primarily as data integration experts, rather than acknowledging the diversity of developer categories that need to create integrations regardless of the extent of their knowledge about integrations.

Diversity of users for cloud integration solutions isn't going away. More roles in organizations want and need to work hands on with data management functions to help generate the datasets that they need for their jobs and their business objectives. So the vendors that step up and deliver what different users require will take cloud integration platforms into the future.

Just like any user experience challenge, the gateways to integration solutions - user interfaces – have to work well for each category of user. So vendors have to understand a lot more about the different kinds of users who want access to integration solutions and about the user experience they should have, to ensure the success of all users. For cloud integration platform vendors, providing outstanding user experiences – for diverse users – is an invaluable differentiator

 

Image source: http://synergy.kuniv.edu/

 

About the author: Julie is an independent consultant and industry analyst for B2B software solutions, providing services to vendors to improve strategies for customers and target markets, products and solutions, and future direction. Julie has expertise in several solution spaces including: data integration and data quality; analytics and BI; business process, workflow and collaboration; digital marketing, WCM and social media; and the pivotal importance of user and customer experiences. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective

 

Data for Everyone? Self-service Data Integration

Part 4 of a multi-part series on the essential interwoven nature of Business and Modern Data Integration

 

                                                   

 

The notion of self-service data integration has been around for a while, somewhat hand-in-hand with self-service BI – both primarily coming from the perspective of power business users like data and business analysts. But a door also opened for less-technical LOB business users to participate in data integration activities. SaaS and cloud services introduced self-service data integration where SaaS providers or third-party vendors supply wizard-like UIs for basic pre-defined integrations or data synchs between specific applications. This version of self-service DI gained impetus from the Salesforce ecosystem of data integration services, many of which targeted "everyday" business users.

Data Integration as a Service seemed to be a new force for the democratization of data. However, when looking at current modern data integration solutions, it appears that tech-savvy business users are the main focus of self-service DI capabilities. So what has happened to data integration for everyday business users?

 

 

 

 

 

 

 

 

 

 

 

 

 

Data for Everyone?

The democratization of data has a place in Modern Data Integration, as both conceptual and actual future directions for solutions. Such democratization is meant in the context of sharing data more widely throughout the organization, connecting many more people to the data they need (not just upper level executives). Organizations thrive and sustain success with better and faster availability of the right data at the right time.

Democratization of data includes self-service data integration and other data services, such as data preparation, that can give business users more hands-on access to data, frequently without the direct intervention of IT. But it would seem that there is quite a ways to go to actually connect different kinds of business roles to the appropriate self-service data integration tools. There has been way more talk than actual availability of such solutions.

Of course, it will take very sophisticated technology behind the scenes to keep it simple in the UIs that give everyday business users access to data integration capabilities. A lot of work must be done, especially to build in the safeguards to keep less technical business users out of trouble. To ensure that everyday business users do the work correctly and avoid serious missteps, self-service data integration has to be narrowly defined, with guidance at every step.

Cloud data integration and data prep solutions support dynamic data catalogs or libraries that provide "certified" data sets that can work well for self-service DI. The resulting data sets are available to the appropriate user roles, including the less technical. Governance of which roles access what data furthers the democratization of data in a risk-controlled environment. It's important that business and IT teams continuously validate the contents of such data libraries, as many data sources come with a short shelf life of relevance.

 

 

 

 

 

 

 

 

Data Governance for Everyone

Self-service data integration is clearly moving forward, and it must go hand-in-hand with self-service governance. There is real risk associated with self-service DI that must be addressed through centralized IT management and governance, which need to be in place to prevent piecemeal and poorly managed efforts scattered throughout an organization. Cloud-based self-service data integration solutions are well-positioned for governance that maps into overall organizational data governance practices and policies.

But remember: data governance is more business than tech: business people are essential for implementing successful data governance. Once again, the crucial partnership between business and IT is a core piece of data governance to make sure that it will work well and make sense both for business needs and objectives, and IT management of self-service DI activities.

 

Data Prep Solutions – Blazing a Trail for Self-Service DI for 'Everyone'?

Data preparation vendors have very effectively shared studies that highlight the costly nature of getting data ready for use by organizations: identifying the right sources; cleansing and validating data; testing for context and relevance; creating the appropriate integrations. Business and technology teams alike are better understanding why data integration and data preparation matter, and why they must be done well. These are not trivial undertakings, and require sophisticated technologies to produce the usable data sets greatly needed for many business activities.

An extensive array of data preparation technologies have emerged to help connect more business people to the data they require for analytics and BI, seeking to greatly reduce onerous preparation time to generate that data. Data integration and data prep do have intertwined destinies, since the goal of either should be reliable, business-ready data. Data prep draws on data quality processes that are have been very much part of data integration for quite some time, as has data lineage.

It looks like data prep solutions are creating the next level of tools that more quickly achieve reliable data, by utilizing applications of newer technologies like machine learning. Data prep offerings incorporate focused machine learning / algorithmic capabilities to automate more of data testing and quality as well as approaches to data integration.

Obviously a core aspect of data preparation is self-service through SaaS / cloud platforms. The vendors behind these self-service offerings are clearly interested in extending the variety of roles, both business and technical, that can take advantage of data prep platforms. Right now the primary users are very technical DI experts and tech-savvy business analysts. But various vendors are working to include less-technical LOB business roles, as well as LOB developers. And these vendors do seem to understand that different user roles require different UIs, capabilities, guidance and governance, and access to data.

 

Self-Service Options and Modern Data Integration

We are seeing significant changes in integration processes, where data flows from and to anywhere: on-premises, cloud, partner systems, third-party enrichment, and so on. With Modern Data Integration, application and data integration are converging to provide everything organizations need in a comprehensive platform. Ultimately for business needs it's still all about the data.

And it's about more people in the organization gaining faster access to data to help them do their jobs better, with improved effectiveness and innovation for the business. Through cloud-based platforms, self-service options can be available to all kinds of roles in an organization.

Self-service data integration is an important goal or Modern Data Integration. But self-service data integration - and preparation - still has a long road to travel before data can be accessed by "everyone".

 

Image source: linkedin.com

 

About the author: Julie is an independent consultant and industry analyst for B2B software solutions, providing services to vendors to improve strategies for customers and target markets, products and solutions, and future direction. Julie has expertise in several solution spaces including: data integration and data quality; analytics and BI; business process, workflow and collaboration; digital marketing, WCM and social media; and the pivotal importance of user and customer experiences. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective

Data Connectivity in the Web-Enabled World

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As the use of SaaS and cloud services has grown, the API (Application Programming Interface) has come to the forefront as an important technology component in this web-enabled world. APIs are points of entry or connectivity methods, for integrations between different services, systems or applications. Extensive documentation is made available to assist developers, to quickly and effectively work with an API.

Actually APIs have been around a long time, and have been used in data integration processes when other connectivity was unavailable. Both APIs and data integration have come a long way since then. Pre-built connectors for innumerable data sources and formats comprise 'table stakes' for today's data integration requirements. As such, developers and users can quickly set up API connectivity to simplify the sharing of data between: cloud services and mobile apps, data integration processes and data repositories – and enterprise applications residing anywhere.

 

The Web API Economy

A detrimental side effect of the fast growth of SaaS applications and cloud services has been the propagation of endless data silos in the cloud. Vendors for cloud applications provide APIs to enable users to access that data, which unfortunately results in the propagation of endless proprietary APIs. Mobile apps have added another front for the non-stop creation of APIs. While many APIs are available to third party developers as "open" or public APIs, underneath they are frequently proprietary to each vendor and not necessarily "open source".

Vendors for SaaS and cloud services have been able to find advantage in their APIs, both for their own purposes and to benefit their users, beyond accessing their data. APIs have become an economic factor that is opening the door to third-party innovation and developer communities. When vendors provide APIs, technology partners and other developers can create new applications (data mashups, for example) that extend the value of vendor services. Mobile apps in particular need such mashups to quickly and seamlessly pull in information that often comes from multiple sources.

Vendor companies are taking advantage of the APIs they have created to build their own digital sites, mobile apps and even internal business processes and applications. Slowly tools are appearing that enable business users (with good tech savvy) to work with APIs -- following the lead of emerging self-service options for business users in data integration and analytics. So the API Economy is evolving to help different roles get a lot more from web-enabled applications and services.

 

Web API Management

Numerous software vendors have found opportunities in providing API Management platforms or solutions. At the high level, these solutions support:

• Development, publishing and documentation phases
• Creation of integrations through pre-built connectors
• Various deployment and customer usage activities
• Overall management and monitoring of API events and services
• API life cycle management

The primary customers have been companies that create web APIs, but third-party users and partners also interact through API management platforms. These platforms make APIs available to third parties, through a regulated and secure interface.

 

API Management for All APIs

For all the buzz about the API Economy and extending services, ultimately a lot of the value of APIs is in connecting to, aggregating and integrating data for more innovative business use. What's exciting about the API Economy is that it's making it easier to use APIs, even for less tech-savvy business users. When offerings begin to include access for business users, it means that the tools are more streamlined for in-house developers and third party solution providers – translating into faster time to implementation and more time for innovation.

Somewhat ironically, the developers and third-party users of web APIs are now folding in connectivity to data sources and applications in the "traditional" enterprise tech world as new ways to leverage APIs. The current notion of what's called API Management will likely evolve beyond the initial focus on web APIs and APIs created and maintained by a particular company, to the broader enterprise world of systems.

 

Image source: cedefop

 

This post was brought to you by IBM for MSPs and opinions are my own. To read more on this topic, visit IBM's PivotPoint. Dedicated to providing valuable insight from industry thought leaders, PivotPoint offers expertise to help you develop, differentiate and scale your business.

 

About the author: Julie Hunt understands the overlap and convergence of many business processes and software solutions that once were thought of as "separate" – and how this impacts software Vendors and Buyers, as well as the strategies that enterprises implement for how technology supports the business and its customers. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting

 

 

 

Interoperating Services are the Heart of Cloud Data Integration

 

Most SaaS offerings started with a business user focus, providing applications that zero in on solving specific business problems. It's become an everyday occurrence for businesses of all sizes to migrate many of their needs to SaaS.

There are also SaaS applications that serve as components of a comprehensive IT landscape. But when we look at creating and maintaining the overall technology infrastructure in an organization, a single SaaS application really isn't able to provide full-on IT services. So IT has been finding more usefulness in the world of cloud services that have their roots in supporting IT and developers. IT is able to take advantage of cloud-based platforms, such Infrastructure as a Service, for core technology tools.

Obviously, in terms of data and technology interoperability, SaaS and cloud services must integrate with the entire IT world, much of which is still on-premises. Business processes and data-flows now run from cloud to on premises and back. Businesses need agile technology tools to handle the increasing hybrid infrastructures of many organizations.

The overlapping of data and application integration has been accelerating, particularly with the growth of cloud-based integration solutions. Out of this convergence has emerged the cloud integration platform iPaaS (Integration Platform as a Service). iPaaS is evolving into a new class of technology that supports hybrid infrastructures, and both business and IT users.

IPaaS has its origins in Data Integration as a Service targeting business users, and in data integration solutions for the proliferating silos of data in the cloud. It has been growing into a platform that also offers services for IT and developers, to more deftly handle multiple integration scenarios. iPaaS often functions as an orchestration hub for complex integration processes. And it is increasingly taking on more "traditional" data integration scenarios.

With iPaaS, business users can handle more of the basic integration tasks through self-service data integration, taking the load from IT and data management teams. And IT is becoming more in tune with the self-service economy, by taking advantage of pre-built, reusable services that speed up the creation of more complex data integration processes. Through a services approach to data and application integration, IT can more quickly keep up with business demands.

For the service economy, iPaaS has to be more than just another development platform for the tech savvy. The ultimate outcome of iPaaS should always be the creation of services – iPaaS itself is a means to an end. The services created contribute to iPaaS serving as an orchestration platform that can accomplish a great deal for organizations:

• Continue to grow the IT-Business partnership by using iPaaS as the means for business users to plan, design and execute integration processes; and by using iPaaS as a collaboration platform for IT and Business to improve any and all integration processes to more quickly meet dynamic business needs
• Utilize iPaaS services to streamline management of integrations and API environments from beginning to end
• Create a single environment where numerous technologies converge and interoperate with centralized management
• Engender the growth of transparency and insight for improved operational intelligence

While iPaaS solutions have evolved tremendously over the past few years, there are still miles to go. Several vendors have realized that with the disparate variety of data and business usage for integrations, critical functions like data quality, data governance and master data management must be added as core services for iPaaS. API management is another critical component, particularly since cloud services have a tight relationship to the development and usage of mobile apps that create and consume large volumes of data.

 

Image source: http://www.wunderground.com/wximage/canon30dguy/19

 

This post was brought to you by IBM for MSPs and opinions are my own. To read more on this topic, visit IBM's PivotPoint. Dedicated to providing valuable insight from industry thought leaders, PivotPoint offers expertise to help you develop, differentiate and scale your business.

 

About the author: Julie Hunt understands the overlap and convergence of many business processes and software solutions that once were thought of as "separate" – and how this impacts software Vendors and Buyers, as well as the strategies that enterprises implement for how technology supports the business and its customers. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting

 

Developing Mobile Business Apps – Navigating Data and APIs

 

Most organizations are well aware that mobile devices and applications are changing how they do business with customers and partners, and how their employees accomplish their work. Mobile business apps are developed to provide useful services that are designed specifically for mobile devices, focusing only on the most relevant streamlined capabilities. Well-designed apps also reflect an in-depth understanding of how different people use mobile devices.

The effectiveness of business mobile apps is ultimately about connecting users to the information and data that they need anywhere, anytime. Business data is frequently stored on multiple platforms, inside and outside the firewall, with varying levels of security and portability. End-to-end task workflows may even take place on multiple platforms. Savvy organizations are catching on that the mobile revolution cannot be stopped. It's best to proactively work out how to govern the mobile tools of the workforce.

Data management and governance, as well as flexible data integration processes, are key components of acquiring and integrating cloud and mobile data with on-premises data repositories. Data in the cloud has been a significant challenge for a while, with each cloud service providing proprietary APIs as the main means for connecting to data. But data residing on mobile devices introduces a whole new world of challenges, including serious security concerns.

As the use of mobile devices and apps for business activities continues to proliferate and fragment data, the standing of data integration as a mission critical technology escalates. What has changed for data integration solutions is the demand for more ways to create and use integration processes. To meet such demand, data integration platforms not only need to be high performance, they must continue to innovate ways to connect to data where it lives and then perform any number of actions to take data where it is needed.

 

Speeding Mobile App Development: API Management Platforms

Agility, flexibility and rapid development are key attributes for the mobile app creation process. Developers of mobile apps have an increasing number of cloud services and platforms that provide reusable components, including numerous JSON and REST APIs that enable data access, as well as the means for navigating security and authentication policies.

Mobile apps both generate and use APIs. On the generation side, APIs that are not well designed or properly built come with a high cost over long-term usage. On the API usage side, in the past, mobile app developers had to embed numerous SDKs directly into the app, which would require constant care and management. API management and integration platforms have been created specifically for mobile app development to orchestrate and enable data integration needs, so that mobile developers don't have to keep re-inventing the wheel when it comes to API creation and usage. These cloud-based integration management platforms cover many of the services that are needed for well-performing mobile apps. Indeed agile API management has become essential for smoothly-running mobile apps.

 

Governance and Security

As with any data-related functions, working with mobile / cloud data integration and APIs requires comprehensive governance and management, to ensure streamlined usability in mobile apps (or cloud services) while adhering to the overall data governance practices for the organization. If an organization doesn't address API management as a critical component of managing mobile app development and usage, many problems can and will result. Security guidelines are also critical for mobile practices.

Ultimately all data usage must in some way align to centralized management to ensure integrated policies, practices and processes across the organization. While the mobile device may be the activity point, the data used and created is still part of a bigger picture. On the other hand, data management practices and policies have to be balanced with enabling the workforce to make good use of cloud and mobile technologies, to more effectively perform work on behalf of the organization.

 

Image source: thisismoney.co.uk

 

This post was brought to you by IBM for MSPs and opinions are my own. To read more on this topic, visit IBM's PivotPoint. Dedicated to providing valuable insight from industry thought leaders, PivotPoint offers expertise to help you develop, differentiate and scale your business.

 

About the author: Julie Hunt understands the overlap and convergence of many business processes and software solutions that once were thought of as "separate" – and how this impacts software Vendors and Buyers, as well as the strategies that enterprises implement for how technology supports the business and its customers. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting

Reducing Risk for Self-Service Data Integration

 

Cloud platforms and SaaS solutions have opened the door to service-oriented strategies for the day-to-day infrastructure and applications needs of organizations. These "off premises" approaches to business functions have helped reduce costs and improve workplace access and productivity. But, as a side effect, managed services providers are losing some of their traditional services domains as companies continue to migrate systems and work activities to cloud services.

There is increasing pressure on MSPs to innovate services in new areas to sustain their businesses, particularly to contribute to real business outcomes (and not just IT infrastructure) and provide more direct business user support. MSPs should consider compelling opportunities for developing "middleware" services that fill in gaps around cloud solutions, especially for helping business users get more out of these solutions, while protecting users and the organization.

Over the years, IT services providers have profited well from building and maintaining data and application integrations for on-premises and cloud infrastructures. Recently vendor offerings for self-service data integration have been growing, with the business user as a primary target. The increased adoption of self-service data integration has the potential to cut into data integration services from MSPs.

Self-service data integration is an intriguing approach to connecting business users to actual integration tools; however this approach is filled with risk that must be addressed. Unfortunately hype from a number of data integration software vendors tries to make the case that self-service data integration is easy-peasy for the business user. The reality is far from this simplified view. But that doesn't mean self-service data integration is a bad idea. And it actually opens up an opportunity for third-party consultants and managed services providers to create valuable services that better support business users – and reduce risk – when working with data integration.

To ensure that business users do the work correctly and avoid serious missteps, self-service data integration has to be narrowly defined, with guidance at every step. MSPs could create a "middleware" services layer for particular self-service data integration offerings that better protects and guides business users when leveraging these offerings. It would be a sort of 'managed intervention services' – protecting and coaching business users when utilizing data integration services, to better understand what is going on and how to use the self-service approach.

Business users have to understand both the business aspects and the technical means to successfully perform self-service data integration. For example, MSPS can provide missing guidance (be assured - there is plenty of missing guidance in these offerings) to help business users utilize data modeling and data definitions that are necessary to stay on the right path for integrations that will correctly produce the data results that are needed. This can be accomplished both through supplemental technology services, and through training / coaching that can be embedded in technology services or handled in live engagements. Internal IT teams often have little time to create such guidance and training for business users.

There are also extremely complex data integration processes that should never be attempted by business users – but these users should have access to the resulting data for their own projects. In these instances managed services can fill the gap by delivering ready-to-use data to business users. MSPs can create the processes that handle complex integrations, making available the resulting data with the assurance that the integrations have been tested and verified by the services provider.

Working with business users for self-service data integration also means that MSPs will now have the mastery to take direct advantage of self-service data integration tools, along with other cloud data integration platforms, to build other data-related services for their clients. There are always numerous data integration projects that are never undertaken because of time and resource constraints for IT and business teams. For many MSPs and consultants, self-service data integration in the cloud can be a faster means to solve data integration headaches for their clients.

Self-service data integration still has a long road to travel before it becomes an everyday tool for many business users. MSPs should look at creating services that help business users today, as well as in the future, to safely and smartly take advantage of self-service data integration as a route to improve the data needed every day for all levels of decision-making, innovation and other workplace requirements.

 

Image source: plexxi.com

 

This post was brought to you by IBM for MSPs and opinions are my own. To read more on this topic, visit IBM's PivotPoint. Dedicated to providing valuable insight from industry thought leaders, PivotPoint offers expertise to help you develop, differentiate and scale your business.

 

About the author: Julie Hunt understands the overlap and convergence of many business processes and software solutions that once were thought of as "separate" – and how this impacts software Vendors and Buyers, as well as the strategies that enterprises implement for how technology supports the business and its customers. Julie shares her takes on the software industry via her blog Highly Competitiveand on Twitter: @juliebhunt For more information: Julie Hunt Consulting

Data Integration Services Evolution

 

 

With the increased usage of data analytics to help solve business problems and improve strategies, data integration has come more to the forefront as a critical component of overall technologies for data-savvy organizations. New approaches and technologies for data integration are coming into play to better meet what organizations need, especially to support increased business user access to data management itself.

Over the past several years, data integration services have continued to grow and evolve, thanks largely to the cloud. Tapping into SaaS approaches, the early entrants were data integration as a service and purpose-built or pre-built data integrations.

 

Data Integration -- as a Service

Data Integration-as-a-service (IaaS) became possible as more organizations made use of SaaS, cloud services and even B2B data exchanges. Business ecosystems began growing in size and complexity thanks to online connectivity, promoting ease-of-access for B2B relationships and interactions. As more data flowed in the cloud, the need and demand for integration picked up momentum. Originally IaaS functioned as an IT-oriented service, mostly in stand-alone instances. But IaaS instances were soon embedded in other cloud services and applications, as well as cloud infrastructure platforms.

The ability to quickly move data to where it is needed must evolve beyond cloud services that only provide basic APIs and web services that still require users to build connections. While leveraging APIs and web services for loosely-coupled integration processes, IaaS rapidly added more sophisticated capabilities such as virtualized data services, governance, REST-ful services, and agile interoperability at multiple levels.

Cloud-based IaaS has since progressed into Integration Platform as a Service (iPaaS). The data integration services evolution now involves comprehensive platforms that leverage cloud services for the creation and execution of integration processes or flows that connect to systems in the cloud and on premises -- within a single entity or across multiple organizations. Services include critical capabilities: data governance and management, metadata discovery, data quality, transformation rules, agile access to data sources – all delivered with automation and ease-of-deployment as important aspects of the overall platform.

 

Purpose-Built Data Integrations

As a more narrow approach to integration, purpose-built data integration is designed to meet a specific business need, with pre-defined capabilities bundled in the solution. Frequently purpose-built data integration comes as an appliance. Purpose-built data integration services in the cloud comprise an evolutionary step for making data integration services available to business users, to initiate integrations between specific sources or applications.

Cloud services for purpose-built integrations usually include data replication, migration, and synchronizations for customer data. Typically integrations involve specific SaaS applications like Salesforce.com and Netsuite as "pre-set" sources and targets.

These services work with focused use cases where business users do not have to make lots of decisions about how the integrations will be accomplished. Wizards are employed to walk business users through the process. However, at minimum, business users must have knowledge of the sources and targets, and basic understanding of the data integration task, to work confidently and accurately through the purpose-built approach.

 

Business Innovation from Data Integration Services

The evolution of data integration services must align dynamically to the business as it changes. Business users require rapid responsiveness to integration needs, through technology that is 'proactively' ready for many use cases that reflect expected and realistic business situations. Innovations for cloud-based data integration services contribute to optimal business performance and to the faster delivery of valuable data that frequently has a short shelf life of relevance.

Data integration services can tap into the rich value of the cloud and how it connects businesses through common services, with business processes providing contextual frameworks. Such data and process agility underpins must-haves for the competitive organization: always-on intelligence, new business opportunities, innovations in products and business models, robust collaborative processes for the ever-growing business ecosystem.

 

Image source: trendmicro.com

 

This post was brought to you by IBM for MSPs and opinions are my own. To read more on this topic, visit IBM's PivotPoint. Dedicated to providing valuable insight from industry thought leaders, PivotPoint offers expertise to help you develop, differentiate and scale your business.

 

About the author: Julie Hunt understands the overlap and convergence of many business processes and software solutions that once were thought of as "separate" – and how this impacts software Vendors and Buyers, as well as the strategies that enterprises implement for how technology supports the business and its customers. Julie shares her takes on the software industry via her blog Highly Competitiveand on Twitter: @juliebhunt For more information: Julie Hunt Consulting

 

Moving Target: Cybersecurity and Integrated Managed Services

 

Cybersecurity continues to encompass the pressing need for detailed, broad and varied solution capabilities. Implementing, maintaining and updating comprehensive cybersecurity solutions frequently seem to be daunting tasks for organizations of all sizes. Simplifying cybersecurity solutions is appealing as a beneficial goal -- but the more useful approach right now is to streamline integrated services to handle a broad range of capabilities. Often different industries require specialized security solutions; customization requirements are often part of the mix for many organizations. Managed services providers can cost-effectively handle these sorts of individualized needs as 'business as usual'.

 

Cybersecurity and the Cloud

Like data management and analytics, the cloud impacts cybersecurity solutions on two fronts: the need to provide extensive cybersecurity capabilities for cloud-based applications and services; and the transition to security services and solutions based in the cloud themselves.

A recent article quoted a survey that revealed the problems still challenging organizations for effective cybersecurity to protect work done in the cloud:

 In the face of rapid growth of cloud infrastructure across IT, security has not been able to keep up with the pace of change. Approximately 65 percent of respondents say it takes three months or longer to deploy a new security solution for cloud infrastructure environments. The survey showed that more than three-quarters of survey respondents experience tool fatigue and nearly as many said traditional tools don't scale well in cloud environments…

The survey showed that 77 percent of security leaders say they have too many point solutions to do security well in cloud environments, and 76 percent say they lack visibility into attacks through cloud infrastructure.

 

 

 

 

 

 

 

 

 

 

 

Image source: CDN

 

 

Comprehensive integrated / bundled managed services can contribute greatly to reducing the complexity of end-to-end cybersecurity solutions, while drawing on MSP expertise in multiple technology areas that matter greatly for effective cybersecurity. MSPs need to develop integrated services that address the needs of both cloud and on-premises technologies and work processes, while utilizing elastic methodologies to better defend overall infrastructures from cyber threats.

Cloud-based cybersecurity services align well with the movement of managed services to the cloud, to increase flexibility and reduce costs in ways that pay off for clients. It's important to remember that cybersecurity is very technology-intensive and can be quite complex 'internally'. While MSPs can create streamlined services that work well for clients, the less viable notion right now is the ability to make cybersecurity "simple" (in the way that basic SaaS services are known for). It still takes well-experienced tech experts on the job to make sure everything is continuously updated and working optimally.

 

Continuous Data Management and Analytics

Data is an integral part of effective cybersecurity services, to build consolidated views across all infrastructures (cloud, on-premises) in order to locate and monitor cyber threats as they occur. Data must be analyzed, understood and put to work to continuously anticipate new threats and improve technologies and processes for better protection over time.

Data sources include big data that comes from many areas both inside and outside the firewall. Big data analytics, combined with other data sources, can process: patterns of behavior preceding attacks; attack attributes; and other analyses -- to derive invaluable context to better understand how cybersecurity services should respond to and prevent threats. Predictive analytics processes lead to crafting methods to head off new kinds of attacks. Big data analytics will take MSPs into more 'creative' services that must continuously evolve and be highly responsive to the ultra-fast kaleidoscope of cyber attacks.

 

Through integrated / bundled managed services that encompass cybersecurity, cloud platforms, and data management and analytics, MSPs can take on all aspects of comprehensive cybersecurity solutions to free up in-house IT teams for other important tasks -- particularly for proactive business technology activities that directly support the business endeavors, goals and objectives of the organization.

 

 

This post was brought to you by IBM for MSPs and opinions are my own. To read more on this topic, visit IBM's PivotPoint. Dedicated to providing valuable insight from industry thought leaders, PivotPoint offers expertise to help you develop, differentiate and scale your business.

 

About the author: Julie Hunt understands the overlap and convergence of many business processes and software solutions that once were thought of as "separate" – and how this impacts software Vendors and Buyers, as well as the strategies that enterprises implement for how technology supports the business and its customers. Julie shares her takes on the software industry via her blog Highly Competitiveand on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective

 

Designing for the ‘Anywhere’ Mobile Workplace

 

For most organizations, business today has a fast pace, is global in nature and relies more and more on virtual networks of employees, partners, supply chains, and outside consultants. Mobile has a critical role here. Mobile is no longer just about devices, it's a catalyst for changing corporate culture that must evolve to ensure the competitive survival of the organization. Mobile is becoming a critical path for providing the workforce with streamlined and secure access to the right data, tools, and applications to do their jobs effectively - anytime anywhere.

Managed services providers have long had expertise for optimizing technology infrastructure, mostly focusing on the technologies and the operations that use them. Mobile is different. MSPs should not only handle the tech services but must understand the big picture culture of a mobile workforce. The underlying services must match all the different ways that a workforce utilizes mobility. End-to-end design services for this new world of work would be an invaluable offering for many organizations.

An outside-in approach to designing the entire mobile experience, including infrastructure, will ensure highest returns to clients in terms of productivity, security and the benefits for desired business outcomes. MSPs can be expert advisers for helping organizations understand the change in "culture" that comes with the 'anywhere' mobile workplace.

 

Who are Mobile Workers? Everyone

Mobility is rapidly becoming a critical element of business technology for many workers around the world. Mobile work activities happen just about anywhere. The classic example has been the "untethered" employee hunkered down in a Starbucks, working away. But today all kinds of employees are actually accomplishing mobile work everywhere: at home, commuting, at client sites or in the field, in libraries or parks. Some are rarely in the office and may not even be working from home. Even traditional corporate office-based employees are shifting more work to mobile devices, and carrying on work "anywhere".

What kind of work flourishes when the mobile office is anywhere? An obvious area is all kinds of services work performed at customer or client sites. Mobility has revolutionized the productivity of such workers in the field. Another category: employees heavily involved in creative work often seek out unconventional sites where mobility connects these employees to the tools they need and to their collaboration partners. Innovative work requires interactions with the world, new ideas, people who are not part of the corporate mindset or even the employee's corporate world. At the other end of the spectrum, effective mobile workers can be those whose jobs focus primarily on well-defined tasks or results-oriented work that fit a fixed set of metrics to show completion and value.

For all of these mobile employees, the work itself will probably become more project-focused. Ever-changing teams of employees, partners, contractors, and consultants will come together as needed, contributing to the needs of such projects.

 

The New Mobile Workplace Still Needs the Human Touch

With the advent of mobility the corporate office environment has started to change. At corporate sites, traditional offices and cubicles are giving way to an increase in casual meeting spaces to support the need for face-to-face meetings and collaborations when truly mobile workers come into the corporate office. Relationships and the focus on corporate goals are strengthened with regular in-person contact. Management and others need to personally interact extensively with mobile workers to understand the value they bring to work communities and business outcomes. While virtual collaboration is on the rise, it's still essential for mobile workers to physically re-connect with fellow workers and partners to take advantage of in-person sessions that tap into the group dynamic.

With this need for in-person contact, the office experience must undergo change. Management must support, encourage and allot more time for interactions between office-bound regulars and mobile workers. Such activity should be considered part of the job. Some of the space that was allocated to offices and cubicles will give way to a variety of meeting areas. But 'untethered' mobile workers also need private work areas at corporate sites. These areas need to have a human touch, again to reconnect these workers with the company that employs them.

 

 

Image source: itbusinessedge.com

 

This post was brought to you by IBM for MSPs and opinions are my own. To read more on this topic, visit IBM's PivotPoint. Dedicated to providing valuable insight from industry thought leaders, PivotPoint offers expertise to help you develop, differentiate and scale your business.

 

About the author: Julie Hunt understands the overlap and convergence of many business processes and software solutions that once were thought of as "separate" – and how this impacts software Vendors and Buyers, as well as the strategies that enterprises implement for how technology supports the business and its customers. Julie shares her takes on the software industry via her blog Highly Competitiveand on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective