Sharpen your sales forecasts
Some organizations have robust tools and monthly processes to help them build and validate their demand forecasts. Others struggle and use simple measures like a 90-day rolling average to inform their purchasing decisions. We can use the Meta-Problem Method to help.
Complex problems are often vague and have many possible solutions. The Meta-Problem Method may lead you far away from the dilemma that started your quest. That’s because the method forces you to clarify what you really want and what you are willing to give up. It enables you to compare objectively the possible pathways and their trade offs. It prevents you locking into solutions mode too early and then doubling down on solving a low-yield problem that does not serve your goals as well as the alternatives. At the end of this process, you will have a better understanding of your priorities and how to achieve them.
Steps in the Meta-Problem Method
Dilemma
The high-level issue you are trying to address
Good inventory decisions to support future demand.
Goal
The changes you want to make to address the dilemma. There are usually many options.
Supporting goals:
- Reduce inventory costs
- Increase profits
Other goals could include minimizing the effort to develop accurate forecasts, increasing service levels to customers, and minimizing waste from expired or old products.
Problem Space
The set of problems you could chose to solve to advance your goals, plus the constraints that hold you back.
Example Problems:
- How could we reduce inventory costs? Maybe the problem to solve is “What inventory levels do we really need?”
- How can we increase profits? Maybe the problem to solve is “Which inventory decisions improve profitability?”
There are many other potential problems to solve related to making good inventory decisions. Each goal has many possible problems we could link to it. Are there other problems linked to these first two goals? Which options come to mind for the other goals?
High-Yield Problems
Sometimes solving one problem helps make progress towards several goals. In this step, we identify these “two-for-the-price-of-one” problems.
Which options will advance more than one goal?
- Developing a mathematical model for sales forecasting and inventory decisions can lead to reduced inventory costs, higher profits, higher service levels, and less waste. However, the models must be tuned to meet business needs, and their accuracy depends on how relevant your historical data is.
- Deciding to accept lower service levels on less important products can significantly increase profitability even while reducing inventory costs and increasing service levels for more popular products. However, some customers will face decreased service levels.
There are many potential solutions that will have varying effects on the set of goals. Which alternatives improve the most important goals? How might the unknown change the right path forward? What other possible solutions are there to address the dilemma?
Problem Selection
Which of the many possible options in the high-yield problem step is the best set to address the dilemma?
- Which solutions make the most sense as a colleague?
- Which solutions will best address the dilemma?
- Which solutions will deliver the best outcome for the least amount of time, effort and money?
Implement, Learn and Adapt
Check continuously that you are still solving the best problem, as new information emerges.
Observe and learn as you go. As new information reveals itself, check continuously that you’re still solving the right problem.