Big data sounds enchanting; however most fail to navigate the data their IT-systems contain, not to speak of making use of it. We believe simple analyses and well-defined targets is the easiest way to start using “big data.”
- Define targets: Want do you want to achieve?
- Prioritize you targets
- Define the data needed for each target
- Use the data
- Reality check: Validate the analyses
- Get ready for take off
1. Define easy-to-understand targets
Without targets your project will satisfy no one: Not you, your colleagues or your boss.
“We need to reduce our stock value by 30%” – this target is a great example of an easy to understand mission
If your team is not ready to make qualified judgments, start with a “project mission” e.g. improved turn-over, working capital reduction, increased service levels etc. and break down the mission into milestones. A helpful way to get from mission to tangible deliverables is by using the cause-effect tree
2. Prioritize your targets
Most likely you want to change too much. Don’t waste resources trying to achieve fifteen targets simultaneously.The joy of achievement is energizing and motivating for everybody. Quick results will convince management that your team deserves resources and priority to execute. Make a simple priority list and start from the top.
3. Define the data you need to support each target
Data is the main barrier and main enabler.
Too little data prevents decision-making and too much data adds complexity.
The need to know everything, in order to start making changes, is an illusion. Therefore, start by using the cause-effect tree to discuss what kind of data you need
In ABC Softwork we have developed a framework with three data levels. Most companies can produce level-one data (~15 columns) and get going with their ABC product analysis. Level-two data (~25 columns) includes data on your suppliers and requires a more mature data production. Level-three data (~50 columns) encompasses data on your suppliers and customers.
The point is that most companies can get to the ABC product analysis relatively easy with a basic data set and when the ABC product data has been implemented, the company is mature and confident to move on to level two and add more data to their supply chain execution.
4. Use the data to create your ABC analysis
When your data is ready (exported from your ERP) , run the ABC analysis and wait for the result.
Most companies are not surprised about their vital few products, but with the number of the trivial many.
Supply chain executives always seems to walk out the door with a common set of priorities after having seen the representation of the portfolio in the ABC analysis.
5. Validate your ABC Analysis and data against ”real-life” and adjust your data accordingly
Companies often find that some of their data is outdated and inaccurate (Read also: How to Identify the 3 classic errors in ERP data) when they run their first analysis. Spend time validating the outcome of the ABC analysis. Why does item XYZ have a negative stock value? Why is 80% of the portfolio handled by one purchaser? How come that item XYZ has no supplier information? The data update and validation is a very valuable byproduct for the whole organisation.
6. Run your ABC Analysis and set up targets for each ABC category to support the overall project mission
Never again one-size-fits-all turn-over rate, safety stock and service level. With the ABC analysis your priorities become more analytical and nuanced. Average values across your portfolio is no longer sufficient, therefore, set up differentiated targets for each ABC category. Start by defining the overall target for your service level. Is your target 95%? Most probably, you want to deliver your AA, BA and CA at a relatively higher service level than the rest. As a result, provide a service level target for your AA, BA and CA products that is higher than the average 95% and a service level that is relatively lower than 95% for the rest, so that your overall average equals 95%.