Supply Chain Disruptions, as we saw them in the last 2-3 years (caused by e. g. COVID-19 lockdowns, the war in Ukraine, climate change, flooding), tremendously impacted so many companies and still do. Given that, the resiliency of the supply chain and with that resiliency of the business is getting more and more important. Clearly, uncovering and subsequently eliminating risks throughout the supply chain becomes a top priority, even on C-level.
The spectrum of risks is huge, going from more logistics-related risks to supplier-caused risks, but there are also dedicated supply chain planning risks. These ones will be in focus here. Resiliency starts often with a well-defined supply chain planning and SAP Integrated Business Planning can help you to get a lot of information about the health of your supply chain.
SAP delivers every quarter innovation with the cloud-based SAP Integrated Business Planning solution alongside corresponding SAP Best Practices content. We now offer some new SAP Best Practices content on supply chain risk management in SAP IBP focusing on supply chain risk management since February 2023. This template contains an example of a supply chain risk story to not only give you guidance on how to build it but also to provide inspiration for your own, company-specific risk management. You can extract here valuable information about potential supply chain risks, and you can illustrate risk areas that result from low forecast accuracy, inaccurate safety stock levels, resource bottlenecks, and excess CO2 emissions.
The Risk Dashboard content we provide here is based on the new analytics stories app which is available in SAP IBP since November 2022. This new functionality leverages the best-in-class analysis and visualization capabilities of SAP Analytics Cloud and allows SAP IBP users to create powerful and user-friendly visualizations to complement the planning capabilities of SAP IBP. The new analytics stories also enable a consistent reporting experience across SAP applications, which makes it easier for users working with different SAP solutions.
What’s the story of our provided supply chain risk management content:
You start with the landing page for supply chain risk analysis. Scores are used to illustrate risks that result from low forecast accuracy, inaccurate safety stock levels, resource bottlenecks, and excess CO2 emissions. It helps you analyze typical supply chain risks and to collaborate with planners to eliminate them.
You see the highest risk score related to inventory.
Landing page for risk analysis
You navigate to the Inventory risk story to understand the root cause. It’s obvious that the inventory targets set e.g., by corporate controlling for cost-saving reasons can’t be reached for the product group MUSIC DOCKS. With a look at the safety stock drivers, you see that the demand variability contributes most to uncertainty in the supply chain and drive the inventory levels up.
Inventory risk story
Forecast error and forecast bias help judge the quality of your forecasting process and are a major input into the safety stock calculations. On the Demand Risk story, you see that there is a very high forecast bias and error for the music docks. This leads to over-forecasting and too high safety stocks.
Collaboration via email
You can reach out to your colleagues directly from the story. They shall create a plan for how much a reduction of forecast error would help to bring down the safety stocks.
Your colleague can start on the inventory scenario story, and directly navigates to the Inventory Analysis app to create a what-if-analysis. This helps him/her to answer the question of what the impact on stocks would be if you reduced the forecast error to 10%? The story can also be used to present the result of the analysis to other colleagues. Here you can explain the improvement of the scenario compared to the base version of the inventory plan. With these results, you can trigger the demand planning department to work on the forecast error reduction to reduce the safety stock, and with that to reduce the working capital.
That’s only one potential story, I’m sure you might think of other stories specific to your company.
We used here some of the nice features to define the stories, like the definition of calculations on top of the SAPIBP1 data model, different types of filters, usage of text for page design, links to other apps in SAP IBP, tooltips to enrich the information shown when chart data is selected and many more.
What are the benefits of such analytics?
Use the existing data in your IBP system to get valuable insights into your business and potential risks
Make it easy for your planners to find the needle in the haystack
Establish a link between data analytics and the planning process
Proactively work on potential issues and reduce risks in production and customer service
Leverage best-in-class analysis and visualization capabilities
Support reporting from within the business application
Offer a consistent reporting experience across SAP applications
How can you use this example?
As mentioned above, this example should give you some guidelines and inspiration. In your company, you might focus on different areas or have additional requirements.
We deliver the scope item content through a presentation describing the setup of the story pages and a video showing how supply chain leads can work with the story.
In the presentation, we explain the model enhancements on SAPIBP1 we used for this example. The Supply Chain Risk Analysis story consists of seven pages:
Risk Analysis Landing Page
To show the nice scores on the entry page, the risk story, we defined for each area (demand, supply, inventory, CO2 emissions) a new key figure e.g., RISKSCOREDEMAND as calculated key figures. Here is the risk score demand as an example:
Risk Score Demand: The risk of your demand plan is measured by forecast error and forecast bias.
- Case 1: if forecast error > 20% AND forecast bias < -5% or > +5%, then the score is counted as 10
- Case 2: if forecast error > 20% OR forecast bias < -5% or > +5%, then the score is counted as 5
- Case 3: in all other cases, the score is counted as 0
In Analytics Stories, the calculated risk score is represented by an indicator chart. Here you can define ranges for the different colors.
For all pages, we describe in detail which data is used, which chart type, which filters, and so on. With this information, you have the base to design your risk story.
Which data is needed?
Of course, you need demand planning data if you want to calculate the demand risk score and the same for inventory and supply. If you want to try it out in a new planning area without data, you can use the scope items for demand, supply, inventory, and footprint analysis including the sample data provided as part of the Best Practices. In the presentation, you can also find a list with links to the related scope items.