Just about everyone in the microelectronics industry is familiar with two patterns: Moore’s Law and the Semiconductor Cycle. These two cycles have taught me the power of patterns and forecasting. Our industry understands how to identify and use patterns to accurately forecast demand, inventory, product development and revenues. Patterns related to demand forecasting not only allow businesses to forecast inventory levels but also helps them better plan revenue and inventory levels, and helps them exceed customer expectations. By tying into the expertise and tools available within our industry, we can better forecast demand, resulting in fewer peaks and valleys in revenue, inventory, and customer satisfaction.
For a company to identify and take advantage of the patterns related to demand forecasting, they need to follow three best practices:
- Implement forecasting software
- Improve processes relating to inventory and sales
- Focus on the customer
At NKK Switches, the design cycles of our customer base can be highly unpredictable. It is not unusual for us to not hear from a customer for more than a year, and then all of a sudden they place an order for multiple products with a request for ASAP delivery. For years, this highly intermittent demand for certain products appeared to be impossible to forecast.
For many companies, this significantly impacts production and lead times. At NKK, this would be a nightmare, as we have more than 8,000 active parts in our electromechanical switch inventory – each of which can be customized based on the needs of our customers. To address this need and get more visibility into our demand forecasts, we implemented these best practices and took a customer-centric approach to demand forecasting.
Implement Forecasting Software
We knew we needed software that could help us identify and create accurate, statistically-based demand forecasts for each of our products. It is nearly impossible for our sales team to account for any distribution patterns for each product because of the high number of switch combinations and unpredictable nature of our customer's design cycles.
As a result, we partnered with Smart Software, who offers Intermittent Demand Planning software. During the implementation process, we not only focused on inventory levels, but also on discovering patterns and cycles that we could identify. We integrated the forecasting software with our enterprise resource planning (ERP) and databases as well as our supply chain management systems.
Tracking each of the products allowed us to generate thousands of possible scenarios for future demand. In turn, this helps us make sense of the seemingly random activity and ordering patterns of our customers and to identify a reliable forecast.
Improve Processes Relating to Inventory and Sales
We now meet regularly with sales and purchasing to review processes, forecasts and the intelligence we input into the software. Using the ERP system, we tracked actuals against forecasts obtained from the Smart Forecasts application over a twelve-month period. We found that our forecasts, particularly in the aggregate, were exceptionally accurate. Actual demand was within three percent of our forecasts and our inventory levels have gone down about 15%, more than covering the cost of the software and changes to our processes.
As a result, we can plan for and start production based upon forecasts, even before the customers place orders because we are able to see what will likely occur and approximately when based on these patterns. In turn, this has led to shorter lead times and happier customers.
Focus On the Customer
While the promise of shorter lead times is a goal we're continuously looking to improve, the opportunity for better customer service has also been uncovered. We've always had high customer satisfaction; however, demand forecasting allows us to stock inventory appropriately without waiting for a customer, and without having too much or too little inventory on hand. Our manufacturing facilities can start to procure raw materials when demand for them is forecasted.
Because we have a better mix of the right inventory on hand and at a time when our customers need it, our customers are happy. Lead times have decreased, we have seen lower reorder points and higher service levels. With reduced inventory, we now can spend fewer resources managing inventory and streamlining purchasing processes to focus on other areas that relate to customer service resulting in reduced lead times, improved on-time deliveries, and other customer-centric activities that give us a strong competitive advantage.
Let us know how you are using demand forecasting and what successes and pitfalls you've found.