Current State of affairs

Digital transformation seems to be a buzzword at the moment in business. Everybody is talking about Digital transformation and planning for the big change that Industry 4.0 is bringing. Yet, very few seem to be actively transforming their business to be able to take advantage of the opportunities it brings.

I have the dubious privilege of having been working prior to the invention of both the personal computer (PC) and applications such as spreadsheets and word processors. Since their arrival, there has been an explosion in the use of spreadsheets to plan all areas of businesses large and small. While this has delivered significant value it doesn’t come without some disadvantages. This blog describes these drawbacks and discusses one alternative planning platform, Anaplan, which can retain many of the advantages of spreadsheets while avoiding the negative aspects.

Master data is an important pre-requisite for achieving good planning results. Like any other system, a successful SAP Advanced Planning & Optimisation (APO) implementation relies on having good quality master data. When projects go-live we always get good results but over a period of time, the quality of results tend to deteriorate due to poor master data hygiene. This is especially true when the SKU churn is significant and the supply chain networks are large.

In this blog, I will outline the features of the Master Data Check Tool developed by Olivehorse.

Anaplan is the latest cloud platform which enables organisations to efficiently collaborate within all areas of the business. With the vision to connect people, data and plans in real time coined ‘Connected planning’. The software enables firms to create dynamic, collaborative and intelligent plans that drive confident business decisions and help’s business accommodate today’s business planning needs

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.

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 offered

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.

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.

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.

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!