What is the Role of the CIO in Driving Enterprise Analytics?
When you talk to CIOs today about their business priorities, the top of their list is better connecting what IT is doing to business strategy. Or put another way, it is about establishing business/IT alignment. One area where CIOs need to make sure there is better alignment is enterprise analytics. CIOs that I have talk to share openly that business users are demanding the ability to reach their apps and data anywhere and on any device. For this reason, even though CIOs say they have interest in the mechanisms of data delivery–data integration, data cleanliness, data governance, data mastering, and even metadata management — they would not take a meeting on these topics. The reason is that CIOs say they would need to involve their business partner in these meetings. CIOs these days want you have to have a business value proposition. Given this, CIOs say that they would want to hear about what the business wants to hear about.
- Enabling new, valuable business insights out data to happen faster
- Enabling their businesses to compete with analytics
CIOs as an analytics proponent versus the analytics customer
So if the question is about competing with analytics, what role does the CIO have in setting the agenda here? Tom Davenport says that CIOs–as I heard in my own conversations with CIOs–have good intentions when it comes to the developing an enterprise information strategy. They can see the value of taking an enterprise versus a departmental view. Tom suggests, however, that CIOs should start by focusing upon the analytics that will matter most to the business. He says that IT organizations should, also, build an IT infrastructure capable of delivering the information and analytics that people across the enterprise need not just now but also in the future.
Tom says that IT organizations must resist the temptation to provide analytics as an add-on or a bolt-on basis for whatever transactions system have just been developed. As a product manager, I had a development team that preferred to add analytics by source rather than do the hard work of creating integrative measures that crossed sources. So I know this problem firsthand. Tom believes that IT needs to build a platform that can be standardized and integrate data from more than one source. This includes the ability to adapt as business needs and business strategies change.
Making this an Enterprise Analytics Capability
In the early stage for analytics, IT organizations need to focus more upon a self-service approach. But as the business matures at analytics, Tom says that IT needs to shift gears and become a proactive advocate and architect of change. Tom says that IT should be a part owner of the company’s analytical capabilities. IT managers, therefore, must understand and be able to articulate the potential for analytics being created at an enterprise level. At the same time, the IT staff–which often lacks the heavy mathematical backgrounds of analysts–needs to be able to interact with the analytics pros who use and consume the information that IT creates to build models. I had this dilemma first hand where my analytics modelers were disconnected from BI product developers. They were two different communities working on our project. And although some modelers can build apps or even a BI system, what excites them most in life is building new analytical models.
Talk the language of the business
Tom Davenport says that IT managers can make their own lives easier with the business and the with analysts by instead of discussing cloud computing, service oriented architecture, or even OLAP, discussing decision making, insights, and business performance. Meanwhile, Tom feels that the enterprise analytics journey starts with good, integrated data on transactions and business processes managed through enterprise applications like ERP and CRM Systems (Analytics at Work, Thomas Davenport, Harvard Business Review Press, page 51).
Focusing on the big questions and the right problems
Clearly driving the business to focus on the big questions and the right problems is critical. IT cannot do this but they can facilitate it. Why does it matter? An Accenture Study found that “companies that derived any real value from them (their analytics) had anticipated how to leverage the information to generate new insights to improve business performance. (“Using Enterprise Systems to Gain Uncommon Competitive Advantage, Accenture, page 3). This is critical and too few organizations succeed in doing it.
With this accomplished and to achieve the second goal, IT needs to be eliminating legacy BI systems and old spaghetti code as well as silo data marts. The goal should be to replace them with an enterprise analytics capability that answers the big questions. This requires standardization around an enterprise wide approach that ensures a consistent approach to data management and provides an integrated environment complete with data repositories/data lakes, analytical tools, presentation applications, and transformational tools. This investment should be focused on improving business processes or providing data needed for system of systems products. Tom says that IT’s job is to watch out for current and future users of information systems.
So the question is where is your IT organization at today? Clearly, it is important as well that IT measure enterprise analytic initiatives too. IT should measure adoption. IT should find out what is used or not they are used. I had a CIO once admit to me that he did not know whether currently supported data marts were being used or even still had value. It is important that we have these answers. Clearly, being close to the business customer from the start can limit what this CIO discussed.
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Author Twitter: @MylesSuer