To put data and analytics to work usually requires multiple roles, not just one, to achieve ongoing value and to align with company functions. No one person can provide all the skills and expertise that are needed. A variety of viewpoints, knowledge and experience need to come into play to get the most from processing and analyzing data – and then to correlate analysis with other information sources and knowledge -- to derive the best overall insight and recommendations.
With the increased interest in big data and advanced analytics, there has been much discussion of the data scientist role. While the data scientist can provide significant value, not all companies will choose to add data scientists. Midmarket companies in particular may not want to invest in this usually expensive professional. But midmarket companies can turn to several existing positions to grow company expertise for data management and analytics. Companies can expand roles for business analysts and LOB users who are more deeply involved in data integration, data quality, analytics and the business processes that create and consume data. Several C-suite roles also need to become proactively data savvy.
Enhancing existing data-related business roles can be a means to better connect technology to business needs and desired outcomes, where many of these roles are strategic and straddle both business and technology activities. Expanded roles for business users are needed to include valuable domain expertise, business insight and real world judgment for analytics and decision-making processes.
Conversely, business users must expand their knowledge of data and analytics to better support their technical partners, so that the most effective activities take place to produce the most useful results. Midmarket companies should seriously invest in developing the skills of multiple roles to better understand data management and analytics – over time this investment will pay off quite well.
In companies where employees understand more about data and analytics, often less time is wasted looking for the right reports or debating whether the right data has been utilized. More time is spent on analyzing the results of analytics and on improving decision-making processes. More employees can be involved in spotting trends and potential problems, to more quickly and proactively manage issues and take advantage of market changes.
The more the consumers of analytics are involved with data management and analytics processes, the better the outcomes. For example, traditionally the strategic executive dashboard has been seen as the "killer app" for most CEOs, where the CEO is usually the 'passive' recipient of intelligence, rather than a participant in its creation. But the growing importance of data and analytics for most companies now calls for CEOs to have a more participatory relationship with the initiatives for generating intelligence and insight, including processes for continuous improvement and constant review of requirements.
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This post was brought to you by IBM for Midsize Business and opinions are my own. To read more on this topic, visit IBM's Midsize Insider. Dedicated to providing businesses with expertise, solutions and tools that are specific to small and midsized companies, the Midsize Business program provides businesses with the materials and knowledge they need to become engines of a smarter planet.
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