Making visual process variations puts the nail on the head.
Not all processes (especially in an ERP environment) can be subject to uniformisation.
Let’s take by example the (simplified) process Order 2 Cash (customer orders products/services, services are delivered, customer receives a bill).
All is well, perfectly implemented, functional it works all right. The order will be billed, customer receives his goods.
But in fact what we do NOT know is what’s happing in real life:
The red arrows shows what is happening in real life (hidden, calls between departments), not supported by the standard flow. But in fact done by the representatives to deliver at their best.
When “create bill” sales needs to verify the sales order … to have the quantity ordered, to obtain the negotiated unit price …
When “check availability” the warehouse mgr contacts sales … to know what kind of goods needs to be packaged.
Meaning: these are deviations of the standard flows.
- how many activities are not First Time Right
- how many fulfilled 100%
- what’s the time spend to get it 100%
- what kind of process steps have been used to get it done
- express these variances in time, in money per activity
Now, we might calculate the Cost of Poor Quality to understand the deviation or variances of the processes, then to address continuous improvement and change the process.
One specific step in this analysis is to measure per activity automatically the disbenefits (read losses) of this.
- Number of bills not 100 % fulfilled First Time Right
- Number of orders not 100 % packaged
Compare this with the total orders, total bills … and take into account the losses (KPI reporting).
Imaging we have a solution at our hand counting the number of deviations, tracking all deviations at no matter what activity. The detailed analysis report might be:
- You are not working First Time Right for process xyz, there’s a bad KPI of 70 %
we suggest to alter the flow …
- You are losing n € / order due to inappropriate processing
Your analysis report might be delivered automatically and feed your continuous improvement steps.
Big Data is much nearer to you than ever thought.