Analytics Competency Center

28 09 2009

We spend a lot of time on Business Intelligence, Master Data Management, Data Governance, Standardization, off-shoring, etc., yet I rarely hear organizations spending time and energy on analyzing the data.  We have cubes, we can do all sorts of things with reports and dashboards, yet I still hear people say “I need more information!”

It is impossible that we are short on data!

  • How then are we not getting enough information out to the organization?
  • Is it possible that we are spending all of our time and energy on data preparation and data movement?
  • Are we creating value, or just planning to create value?
  • What about creating a center of excellence around the business user?
  • Or something around the levers of the business?




Business Intelligence vs Business Analytics

14 04 2009

There is a growing debate over Business Intelligence vs. Business Analytics and what the future holds.  Clearly the Business Intelligence world has been shaken with Hyperion, Business Objects, and Cognos all now smaller parts of bigger companies.  This has created a number of marketing opportunities for the likes of Microstrategy and SAS.  The obvious marketing play was independence.  Now it is clear that SAS is taking a slightly different tact by claiming that Business Intelligence is dead and the future is Analytics.

Marketing messages aside, what we need to be focusing upon how we use information and the management process.  Call it data, information, intelligence, analytics, or whatever we come up with next, it is all irrelevant if we don’t understand how to use it.  A basement full of great tools doesn’t mean the house remains maintained.  
  • Do you have rules on when to use the specific tools in the BI suite?
  • Do your people have the analytical skills required?
  • Do you have a process where the information can be discussed and actions agreed upon?
We all agree that organizations need to make fact based decisions.  The other thing we should all be working upon is creating a common vernacular for each of the tools.  As analysts, consultants, pundits, bloggers, we do little good if we don’t teach the value of how to use each of the tools.  You don’t need predictive analytics for an exemption report.  You don’t need a sexy looking reports that do little to explain the goal.  Organizations don’t need real time scorecards.  

What organizations do need are ways to make people comfortable to take decisive action.  We also need these actions to align to company goals and strategy.  The tools we use need to be consistent enough for us to trust them, and the minds that analyze them need to be able to use the tools well enough to communicate only what matters in a digestible presentation.





Scorecard or Fact sheet

10 04 2009

A common Scorecard design is to list a bunch of business facts – how many customers, total square feet, total employees, inputs, etc.  While these can be important business facts that executives need to know, they may not be manageable numbers.  By adding them to the scorecard, they take up valuable real estate and misdirect focus.  

As you are thinking through your scorecard design, take some time to consider if an item is a REAL KPI, or just a business fact.  Then design the scorecard to focus on objectives with potential links to business fact report(s).





Scorecards & Dashboards

16 03 2009

These are two terms that the BI world uses interchangably. The only thing they should have in common is that they both can visually display data.

Defined:

  • Scorecards are tools that help facilate discussions around strategy and operational performance management. The indicators (KPIs) should foster discussions about corporate direction, resource allocation, priorities, and initiatives. 
  • Dashboards should be used for tactical discussion triggers, like inventory orders, technical support, phone coverage, etc. 

What should be happening with these tools is a far more structured use for each (and throw in reporting as well). All too often these tools are used without discipline which leads to mulitple versions of the truth, lack of focus, red herrings, miscommunication, and ultimately a waste of time and energy.

IT and business users need to work together to better understand what each tool can provide, when that tool will be used, how it will be used, how it will NOT be used, and who should be using them.





Analytics & Actionable Information

5 03 2009

I work on many projects where the outcome is  “just provide us actionable information.” While this is always the goal, I find most people use the term quite loosely, as if it were merely an additional option. In reality this is quite difficult to create. Many things need to come together to create action, and it is far more than just information or a report.

To create effective actionable information, we need to integrate people, information, and tools. We also need to have the right skills at different times. All too often, the expectation is for IT to write a single report that will answer all questions. Yet, what typically happens is the report creates more questions as IT cannot predict every need. All this has done is create more activity for IT and delayed action.

Let’s view this from a process point of view…how would it look:

First, we have a tremendous amount of data. And it would be easy to argue way too much data, hence the need to create layers of relevance. How often do we get lost looking for what we need, or recreate something because we don’t understand the business rules of the data we find? This wasted effort costs the business money and time.

We have the information, now we need a good analytical mind to review the data to create analytical models or what-if scenarios. What typically happens here is a finance or IT analyst runs a few numbers. This is probably OK for many instances, but the best option would be both a mind of the business as well as a statistical curiosity (though at this stage we need more of a statistician). IT and Finance often lack both of these to some degree – as their primarily skill is data or fiscal governance.

Now we have some level of analytical information, but still have work to do. In general, the statistical mind tries to cram in too much detail and wants to discuss the process of discovery, instead of the finding. To transform analytical information into action, we need the business to present the finding in executive terms – value created. The presentation is more than likely to include multiple reports, synthesized into a couple charts. The next step is to foster a discussion of the recommendations and potential options. The discussion will focus on gathering feedback and coalescing them into an agreed upon plan.

It is common here for people not to feel comfortable with the information and ask for additional information and analysis, but we need to fight the urge to delay and put the best foot forward. There will be times when the need for rework is great, but if the discussion includes the right people and the facts then there should be enough to make a decision and move forward. Otherwise, the risk is creating a culture of endless analysis.