Making the Journey to SAP Integrated Business Planning (IBP)
Meet the Authors
⇨ At the Mastering SAP Gold Coast event, Australia's Nuclear Science and Technology Organisation (ANSTO) shared how it evolved from supply chain planning with Excel to a cloud-based model leveraging SAP Integrated Business Planning (IBP).
⇨ ANSTO is able to perform planning tasks previously impossible in an Excel environment, such as customer categorisation.
⇨ With IBP, the organisation has been able to reduce its dependence on imports and is saving at least $1 million per year.
Supply and demand forecasting are critical functions for Australia’s Nuclear Science and Technology Organization (ANSTO), which has operated for over 70 years and currently produces 80% of the nuclear medicine isotopes used in Australia.
At this year’s Mastering SAP Gold Coast conference, Cornelia Boonstra, leader of integrated business planning at ANSTO, shared the story of how the organisation evolved from supply chain planning solely with Excel spreadsheets to a cloud-based model leveraging SAP Integrated Business Planning (IBP).
Forecasting is so important for ANSTO because many of its supply chain components have long lead times, sometimes up to five years, so having a precise view of the future is critical. Also, the high-volume products all have half-lives ranging from six hours to eight days, so timely supply and delivery is paramount.
To manage their supply and demand forecasting, ANSTO started with Excel, where there was no customer or SKU data. It took a financial analyst two days to update the spreadsheet with actuals and months of manually looking at disparate spreadsheets to discern trends and insights. To make matters worse, even if an insight was uncovered, it was scrutinized due to unreliable data.
In 2017, ANSTO attempted to improve its position by spending a year implementing SAP Advanced Planning and Optimization (APO). One IT person was dedicated to the deployment and the organisation stood up a 24-month forecasting tool down to the SKU level. But the resulting solution was still too rigid and difficult to use to support the needs of the operation, so ultimately the organisation returned to an Excel-based forecasting model.
Not to be defeated, ANSTO’s next step was to pursue SAP’s cloud-based IBP solution, which carried the promise of true statistical forecasting capabilities and the ability to generate forecast error calculations. ANSTO did its best to apply its learnings from the failed APO implementation and paid close attention to data integration, ensuring inbound and outbound interfaces between ECC and IBP. The organisation also carefully scoped the deployment to include revenue planning, unconstrained and constrained planning, budgeting, and reporting and analytics. It simplified the design, insisted on robust user acceptance testing (UAT), and required a dedicated planner role in the to-be state.
“We took a measured approach to deploying IBP, starting with the demand module first, followed by the supply module,” said Boonstra. “We held daily stand-up meetings to make sure we stayed on track.”
Looking to the Future
IBP has now been in place for 18 months. ANSTO is able to perform planning tasks previously impossible in an Excel environment, such as customer categorisation. Boonstra’s team can bundle the top five customers together and study actuals and forecasts by this and other strategic customer groupings, thus driving the best supply decisions according to key customer objectives.
With IBP, ANSTO can also rebalance its mix of in-house product output and import products. Typically, the organisation would meet demand month-to-month with a combination of internally produced products and imported products, with the latter carrying significant additional expense. With IBP, the organisation has been able to reduce its dependence on imports and is saving at least $1 million per year.
Boonstra has completely eliminated Excel-based planning at ANSTO. SAP IBP is widely accepted across the organisation as the source of truth for units and revenue. People trust the data. And there is full visibility of customer and SKU details.
So where to go from here? Boonstra noted that there’s more work to do. She wants to further enhance the statistical forecasting capabilities. In the first deployment, there were only 12 months of historical data. The team intends to add more history and enrich the statistical models driving the forecasts. Also, Boonstra is intent on expanding the usage of IBP across the organisation. Right now, her team are the only users, but she sees benefit from other teams like finance and sales becoming users as well. And finally, to dramatically improve data visualization, the future will likely bring a tight integration between IBP and Power BI.