Planning in the time of Coronavirus: Leveraging the power of tools such as SAP® Integrated Business Planning

Posted by Steve Rampton on 01-Jun-2020 14:05:42


First of all, apologies for abusing the title of Gabriel García Márquez’s well regarded book Love in the Time of Cholera. However, it is set in a time of great volatility veering on the apocalyptic which is appropriate to our current situation.

My starting point for this article is that, for the most part, we have had a relatively benign environment economically across the globe for the last 50 to 75 years or so with continuous growth. There have of course been significant disruptions due to wars, famines and epidemics such as Ebola, SARS, MERS and Avian Flu. With the exception of the 2009 Crash, they have generally been contained or limited to one region and economic activity on the whole continued without disruption.




Figure 1 GDP Per Capita

The current SARS-COV-2 pandemic is of a completely different scale and has brought most of the planet to a virtual standstill. Furthermore it is likely to affect economic activity for months and years to come.

Because of this stability, our tools for planning both demand and supply have focussed on dealing with relatively small disruptions – one customer suddenly asking for a lift in demand, a supplier being late with a shipment or capacity on key resources being full. We now face a situation where whole swathes of demand and supply can be turned on and off overnight. How on earth can we respond to these rapid changes with plans that are both feasible and financially optimal?

Below I want to illustrate how modern planning software products can give us the tools to achieve this demanding goal.

Computation without limits

One of my first jobs was working in the Production Engineering Office for part of Dunlop that manufactured parts for aircraft including Concorde and Tornado. All of the times for each operation, be it machining or heat treatment, had to be worked out by hand using just a calculator and machining handbooks. The results were handwritten onto a form and any changes required wholesale reworking.

Luckily technology has progressed a little since then and we are close to the point where compute power and memory are no longer a constraint in most planning tasks as shown in Figure 2 where compute power has being increasing logarithmically since the first computers during WWII. A single card can now have hundreds of cores with many hundreds of gigabytes, but it has been the ability for applications to utilise that power effectively that has been the issue. In the last few years products that can support planning in the Supply Chain domain and leverage this compute power have come to market. One of those is SAP’s Integrated Business Planning (IBP) product which draws on the in-memory storage and massive parallelisation of their HANA platform.wberm-mips-copyFigure 2 Processing power per $ vs time, measured in MIPS and 2007 US dollars: Sandberg and Bostrom (2008)

For the rest of this article I am going to propose how IBP can be used to your advantage to plan for volatile environments.

Demand Volatility

In this section I will discuss what can be done to facilitate large scale changes in future demand. The essential objective of this part of the plan is to produce a forecast for the quantities of each of your products that will be requested by your customers over time. The horizon for this depends on your business but can be anywhere from 3 weeks (e.g. bread) to 10 years (e.g. aircraft). In this environment, the nearer term horizon of the next few months to a year is possibly all we can hope to forecast.

There are several challenges we face as a planner in producing this and for each one I will lay out how IBP can support you:

We’ve lost a whole Channel!

One of the features of the current Pandemic and similar situations is that the measures enacted by different governments effectively shuts down demand from whole countries, regions, sales channels or product types. For example, a beer brewing company will have seen its demand for beer from the on-trade Pubs go to zero during lockdown, but at the same time witness an increase in sales from the off-trade supermarkets. Cooking ingredients such as flour in large pack sizes destined for restaurants will be reduced to those delivering takeaways, but the explosion in home baking has resulted in huge increases in sales from retailers.

So how can IBP help you here? In IBP, although the forecast is stored at customer/product level, the customer data can also be classified by attributes such as region, country, channel and product data by product family, pack type etc. For most of these attributes there is a many to one relationship – for example many customers to one country. So you can think of them as levels of aggregation of an implied hierarchy.

Attribute Star

Figure 3 Example Attributes and Dimensions in IBP

The clever bit is that IBP allows you to enter or change quantities at an aggregated level of one or more of these attributes. The values are then disaggregated down to the more detailed levels below – against a basis you define. IBP takes the strain of these calculations, which for a typical company may encompass tens of thousands of customer/product combinations.

Let’s take an example. I am a company making and selling paint across Europe to Trade and DIY retailers. The UK government announces a lockdown for 3 months that closes all building sites, but DIY retailers can still open. So the forecast for all products taken by customers in the UK in the Trade channel needs to set to zero. In our IBP implementations we normally have series of inputs that allow a statistically derived forecast to be increased or decreased or overridden. So what we need to do in IBP is retrieve the data at country/channel level and then set an override for the UK for zero in all periods we think the situation might persist. The changes made are highlighted in Figure 5 within the red circles. We also anticipate increased demand for a few months after the lockdown is lifted so add that as an uplift. The IBP system automatically applies these overrides and adjustments to all the individual product/customer locations below this aggregate level.

plan beforeFigure 4 Demand Plan before lockdown

plan before 2Figure 5 Plan taking account of lockdown

A lot can happen in a month!

It is not uncommon for demand planning to be performed in monthly buckets – either calendar month or fiscal period. In other words for each product/customer combination there is a planned value for demand in each month from the current to a year or two ahead. This may make sense while demand is relatively stable year on year, and often results in a more accurate statistical forecast, but pandemics don’t follow the calendar. Emergency measures can and are applied and lifted mid-month so there is a need to define plans in weekly buckets. Some companies use calendar months while others use 4/4/5. IBP can cope with either situation as the data is actually stored in what are called technical weeks to cope with weeks where the calendar month changes mid-week. Figure 6 depicts a partial structure to illustrate the way it is constructed.


Figure 6 Time Bucket Structure

Because of this users can switch to viewing and modifying their plans at a weekly level or a quarter at a time. Values are aggregated or disaggregated as required and in extremis you can also define values in IBP to be stored at daily level for even higher fidelity – but watch out for memory or performance effects! The flexibility that this gives should not be underestimated is not possible with many other products.

Can I supply the demand?

One uncommon aspect of the current crisis is that not only are some customers unable to purchase some products, but the ability for the supplier to produce, procure or transport them is also severely limited.

If none of your supply options are available then it is simply a question of working out how long the stock will last and which customers to allocate the stock to. But what if you do have partial, constrained, supply, now or at some point in the future?

IBP allows you to model your complete supply chain network and not only your own DCs and production sites but also customers and vendors along with the lead times between them. The different resources and the bills of materials required for manufacture or assembly can also be modelled. This data can also be taken direct from your ERP system if desired.

Armed with this model and the data on existing inventory, purchase, production and transport orders one of IBPs planning algorithms can be applied. These can be either unconstrained by production or vendor capacity or constrained. If you use the latter approach, the resulting plan will be feasible in that it will try and make use of all possible options for supply until exhausted, even pre-building inventory. The cost based optimiser can even tell you which customers should be shorted based on relative on-delivery costs you define.

This functionality allows you to model several situations that could easily apply to the current situation:

Manufacturing Sites closed:  You may have manufacturing sites closed for a period of time in one country or region due to a lockdown. Initially you can see when the inventory will run out and once you have some idea of an unlock date then you can model the resumption of supply. If you have multi-source options then using any that are still open can be taken account of. The capacity can be set to zero week by week for each resource.

Vendors closed:  Some of your vendors may be locations facing lockdown. You can model the effect of this on your ability to manufacture and as above leveraging alternate vendors.

Effect of Social Distancing: In some cases your capacity will be reduced by the need to conform to social distancing rules. This may be due to a lower number of assembly resources or a reduced line speed. The overall effect of this will be seen on demand and supply.

Unlock Fever:  As your demand side is released from lockdown you may need to respond as fast as possible to a surge in demand from consumers starved of your goods. Alternatively, customers may be reticent to go out to buy or lack money. Hence a slow ramp up to previous levels will occur. In both cases IBP will enable you to produce a feasible and efficient plan.

Options, Political Indecision & Uncertainty

One thing the crisis has taught us, if we didn’t already know, is that politicians really do not understand the complexity of Supply Chains and Manufacturing. I wonder how many have ever worked in a factory or DC? So we cannot expect decisiveness and certainty in the plans going forward. There will be little or no pre-warning of changes. So as planners, we have to look forward ourselves and think of the different possibilities ourselves. We may also have different options ourselves – for example in which sites we open and when. How can we evaluate and compare the different possibilities?

IBP gives you the ability to create multiple scenarios, calculate a plan for each and then compare and contrast. It is pretty cool in that a user themselves can do this in minutes and not just one scenario but several. The user need only change the data that is different to this scenario from the baseline and doesn’t need to copy all the data that is identical. Other Advanced Planning Software, including SAP’s APO solution require significant effort and time from IT to setup anything similar – so much so it is rarely tried. SAPs Excel AddIn is a little restrictive when it comes to being able to compare the results for different scenarios. For this reason we at Olivehorse have developed a tool that allows data to be extracted directly from the IBP system, independently of the SAP AddIn, via OData interfaces and manipulated and enhanced with custom calculations. Figure 7 is a screenshot of one of the setup screens for the tool where cross version/scenario calculations are being defined.

scen comparison tool calc def

Figure 7 Olivehorse Scenario Comparison Tool Setup Screen

Figure 8 shows an example output in the form of a PivotChart but tabular views are also possible.

scenario comparison tool chartFigure 8 Example Chart output from Olivehorse Scenario Comparison Tool

Later on, once the politicians have announced the plan and you have decided on a course of action, you can also adopt the chosen scenario into the baseline plan.

Show me the Money!

In many instances in order to evaluate the impact of a change on your business or compare scenarios you will want to be able to convert the plan into monetary values. We use the word financialise for this. Examples of important values would be gross or net revenue, COGS, contribution and net income from the Income or Profit and Loss statement or inventory ‘value’ for the balance sheet. With IBP it is entirely possible to produce these values – as long as you have the price or cost per unit of volume number required to multiply the quantity by. Your ERP system such as SAP S/4HANA normally has most of these so they can be interfaced into IBP on a regular and automatic basis. These values can be by week, month, period, quarter or year as discussed earlier.

Also that it is highly likely that we will see extreme price volatility as we exit lockdown in order to stimulate demand or to maintain margins in the face of the increased costs imposed by social distancing measures. This can be catered for in IBP as it allows unit prices and costs to be set differently per week or month in the future as well as, for example, by product/location.

Figure 9 below shows a comparison of the results of a scenario versus the base plan that is also financialised.

Scenario Comp

Figure 9 Financialised Scenario Comparison


As the saying goes we live in interesting times. The stability and relative certainty of the past has been replaced by a new environment where volatility and massive changes to companies’ operating models is needed. To cope with the ongoing and significant planning adjustments that result a company with a supply chain of any significant size will need a tool enable this, that is flexible, user friendly, fast and capable of financialising plans. SAP Integrated Business Planning is a leading example of such a tool.

Olivehorse Consulting specialises in the delivery of advanced supply chain tools covering demand, supply and inventory planning. With decades of experience in implementing these tools in some of the World’s largest and fastest moving supply chains and with market leading IBP services and capabilities, Olivehorse are ideally placed to help you plot and execute your IBP journey.

Should you be interested in seeing how Olivehorse can help your organisation, please get in touch now on: 

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Steve Rampton is the IP Director at Olivehorse and has been with the team since 2015. Steve has 15 years as a designer and project engineer in automotive, aerospace and high tech, added to 18 years working in the SAP ecosystem – 7 of which were with SAP as an Engineering Architect.