I recently found a supply chain gem in a quote from
Kathleen Sullivan Garman
“Sales generate revenue, but operations generate profits”, and based on my experience, the way to do that is through an accurate forecasting process #SIOP.
During most of my professional supply chain career, I've heard (and even said many times myself), "Forecasts are either lucky or wrong," but the reality is that this is not necessarily true (even if it has been fun to say it so many times).
Reading the article from
Eric Wilson
reminded me of my struggles forecasting P&L budgets, inventory, and service level capabilities across 20+ countries. The main challenge was not the actual forecast work, but ensuring we had the right data to run the analysis. This has become one of the fundamental reasons for my focus on #SIOP as the basis for operational efficiency, quality, and profitability improvements.
Yes, I was able to successfully forecast, meet, and even exceed multiple times my yearly forecasted goals, but that was based on my knowledge of the company, sales processes, and operational capabilities of the organization across the region. And this (data/knowledge) is something that all forecasters will need as they attempt to answer the executive team's questions about the future.
- Start with your sales forecast (yes, you will need that), but also understand the variance (what I call the “fudge factor”). The historical difference between the sales forecast (before the year started) and the actual sales for the year(s). Does sales consistently overestimate/underestimate their sales capability, and by how much? If there is a trend that you can identify, that should help you understand going forward how to interpret the information you’re receiving as you are working on your supply chain plans and adjust the expectations as needed.
- Reach out to your manufacturing and operational delivery teams (in-house or external) and validate that they can deliver what you need, at the right time, for the right price, and in the right place. There is nothing worse than agreeing to support a 30% increase in sales if your manufacturing team can only produce 20% more at the current costs. Or even worse, you ordered and received hundreds of millions in products that the organization will not be able to sell. Remember the "sales generate revenue, but operations generate profitability"? Here is where you get the profitability part...
- Monitor, adjust, and communicate as needed, early and often. If we have learned anything from the COVID pandemic, it is that the markets can change overnight and that you must be ready to adjust. Forecasting accuracy is NOT a set-and-forget process, and it needs to be quickly adjusted to respond to the changes in the business environment. Is there a natural disaster that can impact your supply chain? Is there a governmental regulation change that can impact your supply chain (remember the “Prohibition”)? Are there any trends that can impact your supply chain, or sales (have you heard about "Swiftonomics")? Are there new environmental regulations, health preferences (smoking or not), or even customer preferences that could impact your supply chain? If any of this happens, you must rethink your forecasting plans, adapt them to the new conditions “and share the information across all of the organization”.
?While every organization may have unique requirements, the steps above can help you develop a methodology that will be aligned with your company's needs and still follow a proven process. If you still have any questions about how to implement supply chain forecasting or a full SIOP process in your organization, please feel free to reach out.
End to end supply chain solutions to reduce cost, optimise inventory, improve customer satisfaction, smarter processes and capability building | Founder & CEO - 7th Mile Shift | Ex-TVS Motor Company - AVP Logistics.
1 年Your views offers valuable insights into enhancing supply chain forecasting accuracy, emphasizing the importance of integrating sales data, operational capabilities, and market dynamics. By outlining practical steps like analyzing sales variance, validating operational capacities, and maintaining agility in response to market changes, you highlight the dynamic nature of forecasting. Considering these complexities, how do you think emerging technologies like AI and big data analytics could revolutionize supply chain forecasting in the near future?
Operations, Supply Chain, Technology and Logistics for E-Commerce. Working on legend status.
1 年Thanks so much for the tag Jorge. I love the "fudge factor". So many times in Ops we rely on absolutes, and we're so focused on the detail that we can forget to step back and see the big picture. When I'm fighting with a spreadsheet or projection, my husband every once in awhile says "I think you're looking at the bark instead of the forest" and he's absolutely right.
Curious about your point 2 - is it better to have an unconstrained forecast and work to improve supply, or constrain the forecast to your current production capability?