Painful report production? Why you should be worried…
The problem with a good Reporting/MI/Analytics team is that they make it all look too easy. They will often go through a very painful report production process (particularly for executive meetings) and deliver against all the odds. This usually involves heroic efforts of chasing, data manipulation and spreadsheet gymnastics. The reports get generated and the Reporting/MI/Analytics team are left feeling burnt out and a bit abused. They complain but no-one listens, as they managed to “get the report out of the door”.
There are a couple of good reasons to listen to this moaning and some simple approaches that can help identify the sources of the pain and help you fix it.
- Why should we care if the Reporting/MI/Analytics team are having a torrid time producing reports?
- What can an embattled Reporting/MI/Analytics team do to show their pain without coming across as a bunch of whingers?
Why should we care, after all that’s what they are paid for isn’t it?
Here’s why you should care about a painful report production process...
A poor production process creates a last minute rush.
- Rushing reports and high levels of manual manipulation increases the chance of errors and reduces the time available to check data.
- Mistakes lead to report-customer mistrust in the data, degrading the value put on it for decision support in meetings.
- Rushed reports give the management accountable for the performance less time to properly understand the data leading to “off-the-cuff” excuses rather than proper insight into what is really going on.
- Heroic efforts and data contortions hide underlying issues with the data production process and mean waste and inefficiency become permanent features of the MI process.
We end up with offices full of people toiling to produce reports that are often casually dismissed by their key users.
A painful production process reduces headroom to create more insightful analysis. Put simply they are flat out producing the “every day” reports and don’t have time to produce the “fancy pants” analytics that would enhance the organisational planning, strategy or decision making processes.
Here's what you can do about it...
Most MI professions will start talking about the software that they really need at this point. In practice automation would be lovely, but often isn’t going to happen in the short term. What can you do to make things better today?
Map the process
Many MI department don’t actually create the data themselves, they are aggregators or scavengers. Often the true source of the data is hidden from view. Walk through the process with the MI production team and map where the data originates and how it gets to the end users. Better still, show the hours of manual labour required for each set of data. Production hours rack up the staff costs and often show overly complex or cumbersome processes.
Document the problems with your measures and data
Rather than letting people mumble darkly “Of course that data is rubbish anyway” write down what the known issues are, what actions are going on to address it and why we bother collecting the information. That way the customer can make a fact-based assessment of whether there is still any value in using that measure.
Add delivery and quality measures to the intra-process steps
If the first thing the internal customer knows about late delivery is when a report is late or doesn’t appear on their desk, it’s going to make everyone look bad. Showing where the delay occurred and who should fix it helps flag the real sources of the problem.
Nail down the definitions
Often the precise way in which a figure is arrived at is not properly documented. This creates uncertainty about what a measure actually shows and increases the likelihood of “key man dependancy” as “no other blighter knows how Jimmy does the monthly complaints figures”. Use a checklist like this KPI Definition Checklist.
Record production issues
Write down, review and discuss production issues, particularly recurrent ones. Aim to tackle the top 3. Engage the teams that have to deal with the fall-out from those problems.
Ringing any bells?
The ideas above are the basics of process improvement, call it Lean, Six Sigma or whatever else you want. Reporting processes are normally overlooked by improvement teams, missing a massive opportunity. Saving headcount in a Reporting/MI/Analytics team can be a messy and slow business. Reducing reporting cycle times, improving accuracy and management confidence can give benefits well beyond a few years of salary savings. There's also plenty of practical help and guidance on how to do this in my book, KPI Checklists...