Impact of data on supply chain decision making
Filed Under Blog
All businesses have to make decisions – it will typically come down to one of two things – subjective argument (“I think this”) or analysis of data (“I know this”).
Let’s think about a few examples
Supplier performance
Subjective – “My production manager is always complaining that they are waiting for parts – my supplier performance must be bad – I’ll send a complaint email to my biggest volume suppliers and tell them I want improvements”
Analysis of data – “I’ve analyzed on time delivery from my suppliers and last month we had 1000 deliveries of which 901 were on time 29 were early and 70 were late. Of the 70 were late – 70% came from a single supplier.”
Supplier quality
Subjective – “The production manager says that we have to scrap large quantities of material because it doesn’t meet spec.”
Analysis of data – “Of 1000 deliveries received 960 passed inspection from our quality engineers, a further 40 were sent back to the supplier as they failed to meet our purchase order criteria.”
With these simple examples it’s easy to see where the robust decision making sits – data analysis should always provide a better platform for decision making than subjective argument however what happens if your system data is flawed and you simply don’t trust it?
How good is your data? Data for decision making
Confidence in your organizations data is key! – arguing with a supplier for improvement in delivery is all well and good but its an all too common experience to find yourself sitting across the table from your supplier with two different sets of data portraying two different situations of reality.
Where does your data come from?
Most companies will have a number of computer systems for executing business transactions from procurement to financial through to human resources – this is where most data is extracted for reporting purposes.
Data integrity can become an issue where incorrect data is entered for transactions (for example the expected delivery date of purchase orders) – without a suitable ongoing data checking/cleansing activity incorrect data can become a real problem affecting decision making.
Getting the most from your data – 6 point plan
1/ Use one system – everyone transacts on the same system (no hidden spreadsheets or databases!)
2/ Check for data integrity issues (run reports!) – if the data’s wrong – fix it!
3/ Centralize management information – get data from one place which means one version of the truth that everyone uses
4/ Adherence to process – focus on clean data being entered into the system (should include system training as appropriate)
5/ Adequate controls over who can enter what data
6/ Data integrity is seen as a serious issue by business leadership