Global distribution issues and increasingly complex supply chains in the aftermath of the pandemic are forcing companies to modernize the tools they use for forecasting demand and planning how to meet it. While a multitude of companies are on SAP APO, set up at least a decade or two back, SAP’s end of support on APO in 2027 is also accelerating the pace at which businesses are now making new planning platform decisions.
It’s a great opportunity for companies to address multiple problems that APO has not been able to address because of an antiquated design that’s now more than two decades old:
- Archaic processes envisioned decades back but not revisited since.
- Lack of stochastic methods taking market signals like customer forecast, competitor pricing, customer forecast, etc.
- Lack of granular forecasts in product, sales and time dimensions.
- Configuration of choice of models within a system is no longer valid.
However, an evaluation and implementation of a supply chain planning platform refresh is not an easy process and takes an average of 2.8 years from vendor selection to complete rollout and from $15-$125 million of spend for implementation and rollout. It means that companies will take time to transition out of APO and they also need to build a strong business case internally and be sure they will reap benefits with new platforms.
This implies that you must be able to prove efficacy of AI/ML, and additional data feeds beyond sales history are required for demand forecasting for improved accuracy.
In the period from now to the three years or more that a company may take to refresh its APO to a new platform, no business leader wants to lose out on an opportunity to improve forecast accuracy. The investment to do so is such that they reap benefits of 10 to 50 times of the investment and the time to value also is low.
To give you an idea about how forecast accuracy improvement is important for a company, Gartner says that a mere 1% increase in forecast accuracy can lead to:
- 9% reduction in inventory obsolescence
- 7% reduction in finished goods inventory (days)
- 2% reduction in transportation cost
Bristlecone, an SAP Gold Partner, has worked extensively with all SAP products over the last 25 years, and we consistently deliver value to our customers. We have designed an interim solution that will improve your APO demand forecast accuracy 1-10% by tweaking the existing process and APO-DP configuration and leveraging advanced analytics.
Bristlecone’s Turbocharge APO solution offers a much faster time to value with shorter deployment timelines and 50 to 100 times ROI.
We have a three-pronged approach to execute this interim solution:
- Process Diagnostics and Re-Engineering: We understand your as-is processes and suggest areas for improvement. To ensure action, we offer support for 2-3 support cycles as well.
- Maximize APO Potential: This includes parameter tuning and process chain rewiring to extract the best out of your current APO setup.
- Demand Forecasting Bolt-On Solution: Bristlecone’s Demand.ai accelerator uses outside data in conjunction with your internal data to generate a more holistic forecast.
WATCH VIDEO: 5 WAYS TO LEVERAGE AI/ML TO IMPROVE FORECAST ACCURACY
While we turbocharge your APO, we’ll also assist you with selecting THE tool for your evolving business requirements, establishing confidence in the promise of advanced models and AI/ML, and building the business case for a planning platform refresh. Our in-house tool evaluation framework will measure different tools based on certain KPIs like tool maturity, TCO, integration flexibility, etc., to help you select the best fit based on your business goals.
We have helped many customers improve their forecast accuracy in APO.
- Automotive aftermarket company was able to improve forecast accuracy by 4% using their POS and channel partner data for demand forecasting as well as by leveraging advanced statistical models.
- Large CPG company was able to overcome challenges of low forecast accuracies in APO with our help by deploying better forecasting techniques and strategies.
- Major garments company was able to see drastic improvements in forecast accuracy and bias by overhauling their APO system and making improvements to their demand planning and S&OP processes.
If you’re looking to transition out of APO but are also keenly aware that this process will take time and you don’t want to lose out on forecast accuracy improvements in the interim, let’s talk. We can help you address your planning platform refresh while improving your forecast accuracy along the way. To know more about our ‘Turbocharge APO’ solution, contact us.
SACHIN SHARMA
Senior Consultant
Analytics and AI
Bristlecone
MANISH KUMAR
Senior Consultant
Business Consulting
Bristlecone
