Monday, February 27, 2012

Analytics as a Strategic Capability

Analytics. The next frontier. First personal computing allowed us to work faster and more efficiently. Then web 1.0 brought an environment that allowed us to work with more flexibility. Web 2.0 made us social and gave us information about who we are, how we behave and what we like. Now it is time for analytics to bring it all together. The efficiency, the flexibility, the information - coming together to generate insights.

While the quantitative tools and techniques that are employed in analytics are nothing new, the convergence of personal computing, the web and social data position analytics to now be a truly strategic capability. The missing piece is organization that leverages each of these components into a cohesive package that delivers the right results to the right people at the right time with the right perspective. This is more than BI, more than a technology. It is a new way of doing business that recognizes the value of information, BUT ALSO is strategic about what problem it is trying to solve, and how that solution is delivered. All this takes people power and smarts that can't come off the shelf, and that understands business strategy, not just quantitative techniques and IT.

The reason why the business focus and perspective is SO important is because with out it, analytics can come up with a million answers, a million solutions, none of which address the real business problem at hand. Many analytics tools on the market make this very hard as they make it very EASY to thrash about in ones data, and to lose focus on why you were knee deep (now neck deep) in it in the first place. It is this axiom that drives the truth that business analytics be driven by business STRATEGY and those that define it. Business analytics should not be driven by technology - in fact technology should be the last consideration. This is not to say that technologists should not be included in the conversation, but they should certainly not be leading it.

So who is this uber businessperson that can lead the analytics of an organization? It is someone that understands technology, quantitative techniques AND business strategy. They are strategic partners with those that set business direction, but yet have the skills to guide or self execute technology and quantitative needs. They must elevate themselves above "number cruncher" status if analytics are to truly shape business strategy. They must see themselves at a business leader more so than a doer. It is this type of leader that can see the big picture and know how analytics fits in that will truly position analytics as a strategic capability within any organization.

Tuesday, January 3, 2012

The Data and Analytics Catch-22

It goes without saying that without data, analytics can't exist.  As such, most organizations invest in data collection systems (ERP, CRM, HRIS, etc), and then get into the business of analyzing the data collected.

Although the main role of these systems is to manage and automate operational business functions, the real value of the data collected is with the analytic insights that they generate.  The problem is that oftentimes analytic needs don't play a major role in these enterprise system implementations.  Compounding this issue is that there is a lag between the time when a system is implemented, and when data actually become available (collected) to analyze.  The result of all this is that analytics can become an afterthought or not practiced at all.

The alternative to this approach is to lead the implementation of a data collection system with analytics.  But how the heck are you supposed to analyze data without a data collection system to collect data?  This is the catch-22.

The reality is that prior to ERP, CRM, HRIS, etc implementations, most organizations are capturing related data in some way (be it spreadsheets, local databases, legacy systems or *gasp* paper records).  These "data systems" while perhaps not elegant, still contain the potential for analytic insights.  What's more is that if analytics, driven by business goals and processes, are practiced prior to enterprise system implementations, then they can sort out what data are really strategic or business critical in addition to operational or regulatory requirements.

The misperception is that big, robust data systems need to be in place before any analysis can happen.  This is just not true.

The message here is that a practice of analytics with available data, ahead of an enterprise system implementation, can lead to a much more informed and productive implementation (among other things).  The key word here is "practice".  Analytics should not be a one time activity or administered only towards a discrete goal (like an enterprise system implementation).  Instead it should be an ongoing effort, employed at all levels of an organization, and across business functions, with whatever data might be available (be they spreadsheets or ERP systems).

Affordable analytic technologies exist today that make it easy to pull data in from these rudimentary and disparate data sources, and blend them together to generate analytic insights that address specific business goals and needs.  The practice of analytics not only enables these insights, but also informs potential investment decisions related to enterprise data systems.

So before you think about that new ERP system, think again!  You might be better served first practicing analytics with data you have right now!