Inventory management is defined as “the planning and controlling of inventories to meet the competitive priorities of the business.” While inventory management is often thought of being beneficial for only large retail and manufacturing companies such as Costco and Kevlar, it is important to realize that smaller companies can benefit greatly from inventory management.
One aspect of inventory management that is particularly useful is forecasting demand. Although not always exact, forecasting demand is necessary to cut costs, meet demand, and eliminate waste. Many large companies have the assets to use sophisticated technology and software to forecast demand and manage their inventory. However, most small businesses have to do it the “old fashioned way” using various methods such as moving averages and exponential smoothing. These methods help to even out demand to allow for seasonality forecasts in the results.
My mother’s company is a full-service hotel design firm. Although hotels open year-round, many owners are in a rush to open during late spring/early summer as well as mid fall due to the high influx of travelers during those peak times. Therefore, it is important for her company to anticipate and forecast the seasonal demand in order to have enough staff on-hand and for her vendors to have enough supplies readily available to ship to the right destination. These methods allow them to not have too many staff or too much inventory as waste and reduces their costs, as well as ensure they have enough product and supplies to meet the hotel owner’s needs.
Are inventory management and demand forecasting more important in a made to order (MTO) service company, like the design business, than in a non-MTO firm?
Again, large companies do not have to go through this process and, instead, are able to use sophisticated technology and software to manage inventory and processes and forecast demand. One software large companies use is the Watson Internet of Things (IOT). The Watson IOT helps manufactures by harnessing the influx of data that is coming from the factory floor and uses condition-based modeling to help record inventory management and asset management. In the video below (1:05-1:30s) you can see the ways the Watson IOT utilizes data. Although it is mostly about asset management and predicting breakdown of machines, I encourage you to watch the full video because the same data and software could be used to manage inventory and store past demand to predict future demand.
How does this relate to JIT and lean processes? Is it viable in the current environment for smaller companies to harness the power of big data and sophisticated software to manage inventory and forecast demand more accurately?