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Many people look at forecast inventory accuracy in the same way people look at the weather. Maybe it’s right, maybe it’s wrong, but there will be more weather tomorrow and we can try again.
But in business, that can cost countless dollars in the form of constrained cash flow as inventory builds, or it can result in lost orders and lost sales as stockouts begin to hit. But the truth is, low forecast inventory can impact inventory levels and valuations in two ways. Either the forecast is off, creating shortages, stoppages, and unfilled orders. Or it is off, and inventory builds until it impacts cash flow, warehouse space, and drives up excess labor costs. And if forecasting accuracy isn’t brought under control, it can result in a self-inflicted “bullwhip” effect.
Low inventory forecast accuracy can impact your operation in several ways:
Trends – If the forecast is inaccurate, then trends cannot be identified. The ability to drill down to data trends can signal changes in consumer tastes and seasonal microtrends not otherwise noticed. With many companies' supply chains stretching to 30, 60, and even 90 days, this can be a disaster.
Overcompensating – When forecast accuracy is poor, planners tend to compensate. Maybe that means backing off based on “gut” feeling. Or it may mean over-ordering to make sure the operation has what it needs. But there is a thin line between compensating and overcompensating. And very quickly, a company can find itself drowning in overstock of some components while starving for others.
Customer Experience – When inventory forecast accuracy is low, customers are the ones that pay the price. Until they don’t. Because if the problem continues or becomes systemic, customers will simply leave, throwing yet another challenge into an already burdened inventory planning system.
To drive out low inventory forecast accuracy, companies can focus on several ways to improve this area.
Proximity – A manufacturing operation is a complex system. And with that system comes inputs and legacy decision-making along the supply chain. By forecasting demand and bringing the forecast as close to the proximity of the customer, planners can ensure that they are ordering what is demanded and not what planners “think” they should order.
Differentiation – Few companies offer one product. By identifying demand based on practices such as ABC analysis, planners can differentiate by product class and type. Once these are broken into their own buckets, they may each have their own lead times and quirks associated with those product lines. This can result in different strategies for different value streams…and different approaches to inventory on hand for each.
Remove the Human Factor – While decisions will always need to be made by people, having a systemized way of smoothing and rationalizing historical data as well as eliminating gut-level decisions and “overstock fiefdoms” can bring the inventory forecast in line with data.
High View, Low View – An accurate inventory forecast will be able to look at the aggregate level as well as the micro-level. And accurate inventory forecasting will tell you which method – or whether both – are required for your organization.
Sharing is Caring – One drawback of traditional planning is that it exists in a silo just as all other relevant data within the organization does. If a company adopts no information sharing (NIS), then the opportunity for forecast improvement is low. If they operate with full information sharing (FIS), then forecast accuracy improvement is more likely. By developing a systemized method for sharing inventory forecast data and the parameters upon which it operates, everyone in the organization can see and act based on that data.
While many companies have traditionally honed their forecast inventory accuracy, there is a plateau past which human action cannot breach. The variables become too complex and the details too in-depth to manage it from more than a macro level.
To bring forecast inventory accuracy to its optimal level, companies should utilize planning software to address their needs. Planning software un-siloes the data, providing planners with access to near real-time information. It also automates as much of the planning process as possible and parses it with advanced analytics to provide more accurate inventory requirements.
But planning software doesn’t stop there. With advanced analytics, near real-time data, and advanced algorithms, it can identify demand trends not immediately obvious otherwise. It can also differentiate with powerful ABC analysis to allow companies to zero in on their most profitable lines and manage their inventory accordingly. By recognizing demand as it occurs, planning software can help plan at the aggregate level while moving inventory planning as close to the customer as possible to optimize the organization.
With advanced inventory and demand planning software from Plex DemandCaster offers Supply Chain Planning, you can manage to a higher degree of forecast inventory accuracy to control costs, fulfill demand, and stay competitive without tying up excess cash in inventory holding costs or experiencing stockouts.