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Data Quality part 2

Posted on: 15-03-2018 16:20:57740

In my previous blog on data-quality I made the statement that cleaning your data is a strategically important (and therefor necessary) task, for the simple reason that without the proper KPIs it is hard to reach your strategic goals and that, when your data isn’t clean, you will not be able to generate the proper KPIs. Without clean data, no proper KPIs, and without proper KPIs you won’t know whether you’re on the right strategic track. Period.
I will focus first on “clean data” as part of data quality, and its effect on waste of time.
In a recent publication on, Bob Vionino comments on a survey of more than 400 data functions in the USA and Europe, quoting some impressive figures.

Clean data

According to the study data workers lose 30% of their time searching for information they cannot find, prepare or protect, and lose an additional 20% of their time building information assets that already exist. So, only half of their time they are trying to get insight. That figure matches my observations in the companies I visited in the further and recent past.
Being positive and based on my observations, I assume that 20% of the first 50% (about a day per week) is spent on figuring out what data is correct and what data is erroneous and getting rid of the erroneous data. Time that should be devoted to understanding and solving problems and issues. Recognizing whether data is corrupt can be relatively easy (e.g. by checking whether a transaction date is long in the past) but can also be relatively to very complex. As an example, in SAP, just try to figure out which materials (stock) are reserved for canceled sales orders with customer specific materials. Experienced MRP planners can do this, because they know the way to look for it. Advanced information systems can do it too, when that logic is embedded into the system.

Closed loop performance

Data quality is more than ‘just’ clean data. One must also know what the data stands for, where it can be used for when you see the data. I have seen many beautiful graphs on KPIs in board rooms and managers’ offices. Giving information about costs, revenues, delivery reliability, and so on. Here’s a challenge. Whenever you see such a graph on the wall with yellow (warning!) or red (bad!) figures, grab the responsible manager (even if that is yourself) by the sleeve, grab the graph and go to the operational people (the girls and guys that make the goods, information and cash flow in the system). Point these people to the yellow and red figures, ask what they can do to get the figures back to green and then keep silent with a genuinely interested questioning look.

I have done that many times and nearly each time I got a variation on the answer “I really wouldn’t know…” Most of the times this is caused by the fact that the operational people use the ERP system as their information base (input and output) and that managerial people use Business Intelligence (BI) system to generate their managerial reports. There is an ‘ETL’ step In between both systems, that Extracts data from the feeding systems (ERP being one of them), Transforms that data (e.g. with statistical or proportional calculations) and then Loads that information into the BI system. That process creates a distance between management and ‘the floor’… they are not looking at the same data. And when they are not looking at the same data (meaning that a KPI is directly connected to the transactional or master data in the ERP system) you will not have a closed loop performance management system. Closed loop performance management systems have a direct link between the KPI (or dashboard) information and the atomic operational and master management data that the operational people use. This allows a drill-down to the details from the graph or pivot in question.

Are there systems that can help you getting more accurate data and that can give you closed loop performance management? Yes… If you are interested, we invite you to have a closer look at Every Angle.

Jacques Adriaansen 
Business Improvement Thought Leader

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