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.

THE IMPORTANCE OF INVENTORY MANAGEMENT

This article explains the importance of Inventory management in achieving a high customer service level with the right inventory.

There is only one way to go: Forward.

The world is constantly changing, things that we could barely imagine a few years ago have now become part of our daily routines.  We take for granted how we use our smartphones, the cloud, and electric cars and many other technological breakthroughs.   For example, 10 years ago it would have been hard to believe for some sceptics, that a smartphone could provide enough computing power to run their spreadsheets or provide a wireless connection fast enough to watch video streaming.

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.