In many organisations, it is very common to use the statistical forecast as a baseline forecast. Understanding and analysing of historical data are very important to generate a reliable statistical forecast. In most of the cases, demand planners rely on their team’s experience and conduct visual check (graphs) to understand historical sales pattern such as seasonality, trend, etc. SAP adds another feature in its SAP IBP software under Forecast Automation application, and through this application, demand planners can analyse historical demand data statistically without being too mathematical. In this blog, I will walk you through how it works and discuss some of its advantages and drawbacks of it.Read Article
In this modern era of globalisation where geographical boundaries are no longer a limitation, with shrinking lead times and increasing speed of business, organisations have a greater need for efficient supply chains than ever before.
In this blog I will explore the collaboration features allowing organisations to plan their supply chains effectively and efficiently.Read Article
The planning capabilities of SAP Integrated Business Planning (IBP) for Response is always compared with a much matured and stable product, SAP Advanced Planning & Optimisation (APO). While SAP plans to discontinue the support for APO in the near future, the businesses have now started looking forward to IBP for Response as a potential replacement for planning in order series. This module is yet to reach the pinnacle of its maturity in terms of functionalities, but the progress has been rapid and the road map looks stronger. Further, it looks promising in terms of speed and flexibility which was not possible in APO.
In this blog I will explore features of IBP for Response & Supply. This includes integration of IBP for Response with external systems and the time series counterpart of it followed by the planning operators being offeredRead Article
For some time now, SAP have been clear with their intention to develop forecast automation via machine learning capability and functionality. With the 1811 release of SAP Integrated Business Planning (IBP), SAP are really starting on their machine learning journey by leveraging content within their Predictive Analytics Library (PAL) and have introduced Gradient Boosting of Decision Trees (GBDT) to the available set of statistical forecasting algorithms within the IBP for demand license.Read Article
For many manufacturing organisations, Detailed Scheduling is mainly driven by the need to perform manufacturing by following a specific preferred sequence whilst generating an achievable finite plan. It is quite normal for companies to use Detailed Scheduling heuristics for this function, but there are scenarios where this does not quite fit the bill.Read Article
I have recently worked on an SAP Integrated Business Planning (IBP) project focusing on implementing an efficient Demand and Supply Planning process (with supporting S&OP layer), where there were many transactional interface requirements between SAP ECC and IBP. In this blog I will explain how powerful the SAP Cloud Platform Integration for Data Services (CPI-DS) tool is in integrating master data and transaction data from SAP ECC to SAP IBP and in passing the planning results back from SAP IBP to SAP ECC.Read Article
During my career I have worked as both a Demand and Supply planner, working across FMCG, Fresh Produce and Cosmetics industries. When it comes to creating baseline forecasts for New Product Introduction (NPI) or phasing out forecasts for End of Life (EoL), planners find it challenging to collect relevant information from various stake holders and spend more time crunching data sets than creating meaningful forecasts.
This blog will discuss the features of SAP's Integrated Business Planning (IBP) Product lifecycle application within the Demand module and how it will help planners to overcome these challenges and help create a more accurate base line forecast. Enjoy the read!Read Article
Forecast consumption is a core to most Planning systems, and is based on the assumption that the actual sales orders consume the forecasted quantities. This approach ensures that incoming sales orders are not treated as additional demand to the forecast during a planning period.
It has always been somewhat of a surprise that forecast consumption has previously not been part of SAP Integrated Business Planning (IBP) for supply as standard, and has only been introduced (time series based) as part of the recent 1805 release.
Prior to 1805, only a very simplistic forecast consumption method could be configured using key figure calculations within the week time bucket. In this blog I will explain the functionalities available within SAP IBP.Read Article
In today’s fast moving world, there is an ever increasing demand for customisation and personalisation, whether it be initials stitched on to your running shoes or a bespoke paint colour for your car. Everyone likes to have a personal touch in their day to day activities, so why should SAP Integrated Business Planning (IBP) be any different?
If you haven’t seen the SAP IBP Excel Add-In, or want to know more about the various functionalities offered, please take a read of this blog from Steve Rampton “SAP IBP Excel Views – A Planners dream?”. I will split this blog as to how Planners can create their own personalised views within SAP IBP in two;
- Basic formatting of the Excel Add-In
- The advanced Olivehorse way!
In our experience, most customers have planning data held on spreadsheets, with e.g. ProdLoc or ProdCust by row and a time dimension in each column, similar to the view below;
But! In order to send the above forecast data into SAP Integrated Business (IBP) via Cloud Platform Integration – Data Services (CPI-DS), there can only be a single row per time period, similar to the view below (note that the data is loaded in to a staging table prior to committing to the HANA database);
Obviously such manual reformatting of data every time a load is required for SAP IBP is a waste of planner time and effort.