US and China have been at the forefront of a tariff battle that’s been going on for close to a year and a half now. Given the economic might of these two nations, the tariffs by both sides have not only affected them but have also had a domino effect on several other countries across continents. A key reason for the domino effect is the global nature of supply chains, a hallmark of the global era we live in.

There are plenty of businesses, across the spectrum, big and small in terms of their revenues in the US that rely on finished goods, semi-finished goods, and components or raw materials imported from China. Depending on a company’s specific situation, they might do things differently. Some might move production outside China. This can be to other countries in Asia, and in some cases, it can be back to the US. Some others might take a more nuanced approach and only move the final assembly out of China. Yet others might be in a wait and watch mode before acting.

So, what does all this spell for supply chain managers and planners? Apart from the need to adjust to the price changes hitherto, there is a great deal of uncertainty about the policies going forward which also needs to be addressed. One of the techniques that could greatly enhance responsiveness and decision making in such times is what-if analysis. It is also sometimes referred to as scenario planning or what-if scenario planning. In a nutshell, what-if analysis allows one to consider different scenarios (of future) and evaluate their viabilities and various implications to the overall supply chain.

Some of the scenarios to consider, like touched upon above, could be to shift sourcing to a different country that is unaffected or look for markets elsewhere (if demand is what is affected), postpone investment on additional resources or capacity, postpone expansion plans, passing on some of the cost to the end-user or even possibly absorb some of the cost. Of course, what is possible in one environment may not work for another and the decisions will need to be well informed and nuanced. Decision making in such situations clearly needs a lot of number crunching. If the business is small, then an excel sheet could do the trick but for larger and much complex businesses there are a lot more variables/moving parts to consider which is why an enabling software becomes important. Some of the key features of enabling software are listed below:

  1. An accurate model of the business – The model should be as close a representation of various business rules as possible. If the model is simplistic then the results may be meaningless. The model, when fed with data, is what simulates the behavior of the system in the future. Sometimes these models are called digital twins as they represent a digital version of the business. 
  2. Data controls – The planners should have control over the data being fed to the model. 
  3. Scenario functionality – Various sets of input data and model output should be able to be stored as separate scenarios for quick comparisons.  
  4. Calculation efficiency and robustness – The calculations behind the model (optimization engine or a heuristic) should be robust and efficient. If the engine takes too long to complete the calculations or if it doesn’t work well for certain kinds of datasets, then it may be ineffective to use. 
  5. Ease of reporting – Users should be able to create various types of representations of the output data or results easily for use in key meetings, 
  6. Ability to collaborate/Multi-User mode – The software should allow collaboration amongst the key stakeholders from various entities in the supply chain. 

Following are some points to keep in mind while setting out to do a what-if analysis:  

  1. User awareness of the model and data – The planner should be aware of the nitty-gritty of the rules in the model to enable understanding of the model results without needing assistance. The planner should also be aware of all the data controls available to make the best use of them. 
  2. Baseline – Before considering various scenarios there should be a baseline available to understand the status quo and be able to compare various scenarios with. 
  3. A clear objective – A clear definition should be made of the questions that need to be answered. 
  4. A number of changes or scenarios to consider – too many changes or scenarios can be hard to analyze and there is a possibility of getting lost in data. A clear objective will go a long way in helping with this. 
  5. Inputs from other teams – This is important in defining data for various scenarios. A clearer understanding of a scenario sometimes needs inputs from other teams. For example, a planned work center shutdown could need input from the maintenance or manufacturing team on the duration of the shutdown, capacity before and after shutdown, alternatives, etc. 

To learn more about What-if Analysis, read Anatomy of a What-If.

In some ways, uncertainty could also mean an opportunity.

What-if analysis, if done correctly, can prove to be a vital tool and enable proactive measures in the face of current uncertainty due to the tariffs and be the difference between businesses that take a bad hit in such situations vis-a-vis competitions that minimize the negative impact or even prosper going forward.