As an analyst, I get to see a lot of product demos (I started to count but it started to scare me how many I see in a year). One of my growing pet peeves is around reporting and analysis. Almost all that I see is what I call a “field of dreams” strategy. If we build a solution that encompasses all of the data required, that calculates all of the potential metrics that users might want, and provides them the ability to drill down and around all of it, then users will flock to use the solution because they will gain so much insight. I think that is why most BI solutions do not get used beyond a select set of users today.
At the end of the day, you analyze data to gain insight so that you can make better decisions and take appropriate actions. The starting point should not be the data analysis, but should be the types of decisions and actions that a particular user needs to take. Let’s look at an example. Let’s say that I am a regional bank manager and I have twenty bank branches in my region. What I might be concerned about are revenues, deposits, labor and facilities costs, profitability, customer satisfaction, etc.. These are business metrics that hopefully are tied to broader corporate objectives. So far, this is relatively straightforward. Let’s now say that customer satisfaction ratings have dropped below a particular target level. I know as a regional branch manager that this drop could be a leading indicator to revenue and profitability (assuming I have a good corporate performance management solution, then I should know the correlation/causality). That is not good. It is getting close to the holiday season and if that metric does not improve, I might not get my holiday bonus. I need to take action to bring customer satisfaction levels back up or I am toast.
This is a moment of truth for business intelligence. What would that regional bank manager do? At best, I might login to the system and see which branch(es) have the problem (or I might even get an alert that tells me). However, do you think they are going to go into a Business Intelligence system and drill down through all of the data to find what might be the potential root cause of the issue? Do you think that the business intelligence system will have drill down paths to all of the potential root cause data? I do not. This user does not have the time (remember, this person is overseeing 20 bank branches) even if they had the skills to do so.
Let’s move to my home turf, Human Capital Management, and assume that I know which branches have a customer satisfaction issue. What employee-related factors might be causing this issue? Most regional bank managers would do a different type of drill-down analysis to figure this out – pick up the phone and call the branch manager(s) in question and ask them what is going on (they might use more colorful language than that) that is causing the drop. The actions taken based on these conversations are not likely very data-based and frequently may be inaccurate (or make the problem worse). That is not good if I want to get my bonus.
In my idealized world, what a business intelligence solution should do is tell me which employee-related factors might be the likely cause of the problem. Has employee engagement dropped? Has 90/120 day voluntary turnover increased? Do the branches have open headcount (are they understaffed)? Has the number of part-time workers increased (maybe they are unhappy about not being able to work full-time)? What is the tenure of the bank management (are they new)? Do exit interviews show that management is a problem (if you saw “Undercover Boss” this week, you probably know what I am talking about)? I think you get the drift. There are many, many more questions that might highlight potential root causes.
What I want the system to do is help me understand which ones are the most likely root causes in this situation. Let me reemphasize this. I do not want to have to do a lot of analysis to figure it out. I do not want to have to call up HR to do some analysis (though that is better than doing it myself). I want the system to do the leg work. I want it to be intelligent enough to ask all of those different questions, look at the metrics associated with those questions and see if there is correlation/causation with customer satisfaction. Then, I want it to present me the results so that I can see the most likely candidates.
Guess what, even at that point, I may not take action though. I likely still will want to discuss the results with the branch manager(s) because the data may say one thing, but reality could still be something different. Once I am comfortable that I know the root cause, then I need to figure out what action (or actions) to take. Maybe the system can suggest potential actions. Maybe there is an online community of senior level bank managers where I could get advice and insight (yes, there could be a social software angle here)? Maybe I would talk to my HR business partner? Maybe all of the above? This is a discussion for another blog post.
The next time you watch a vendor demo of reporting and analysis. You will likely see them do a drill down to find a root cause (in fact, the data is set up so that they will easily find a pre-determined root cause). In reality, they are just applying the intelligence manually. Vendors, consultants and HR professionals have the knowledge to know where to drill down, where the potential root causes may be. Why can’t that knowledge be captured in a system? Why can’t someone design a business intelligence system with actual intelligence about the business domain built-in?
That is the end of the rant. Am I being too harsh? Am I asking for the impossible? What do you think?