Right Product, Right Place, Right Time
This is the goal of every mid-market organization involved in the production and/or distribution of physical goods, is meeting customer demand along with investing the least amount of resources possible in order to fulfill that demand and drive profitable revenue growth. One of the most important aspects of this process is for an organization to understand customer demand in order to forecast what’s needed to make this goal a reality. Demand planning is the cornerstone to success and involves using historical demand to predict future demand.
However, accurate forecasting can be difficult because customers don’t always know what they want or when they want it (but as we all know, they want it now). Additionally, using historical demand to drive statistical forecasting is no longer an effective approach due to a variety of black swan events — an unpredictable circumstance that’s beyond what is normally expected of a situation and has potentially severe consequences. These events are rare, have a severe impact, and yet have widespread hindsight insistence that they were obvious.
The COVID-19 pandemic was one such black swan, but it — along with other economic and political factors — contributed to a number of others, including global supply chain and logistics challenges and long-lasting labor shortages. All of these have turned supply and demand planning on its head. Additionally, the war in Ukraine along with rising inflation and interest rates have made demand planning less predictable. This is not expected to let up anytime soon, with experts still warning of a recession in 2023.
Organizations using historical demand data to calculate a statistical or math-based forecast as the “best guess” for future demand will be at a disadvantage by not accounting for future events and could face negative results such as excess inventory or products that are stocked out where demand is outpacing supply. Even using an internal or external group’s demand plan has risks as they likely have reasons for adding bias to the forecast, meaning over or under predicting demand. For example, a customer generated demand plan might have the intent to over predict demand by 20% to better ensure product is available if they need it. Today, a new approach to demand planning is needed — one that minimizes risk.
The Solution: Collaborative Demand Planning
It’s clear that demand planning using historical data is no longer a reliable method for forecasting customer demand in today’s world. A more informed solution — and unfortunately one that is often overlooked in current practice — is using intelligence from multiple perspectives combined in with statistical demand. We refer to this alternative approach as collaborative demand planning. This is no longer a capability that can be only leveraged by large enterprises.
Demand intelligence can be incorporated by key stakeholders across multiple departments within the organization: sales, marketing, finance, operations, executive leadership and even customers’ insights. Each of these groups understands customer demand from their respective level and viewpoint in the business. For example, sales understands demand at the category level, whereas marketing can provide deeper insight at the item and period levels based on specific promotions and events. The executive team can provide their input at the macro level.
This collaborative demand planning process helps to sidestep a common problem: one person or team from one department or functional area of the business with an inherent bias creating the (or multiple) demand plan(s). When this happens, the demand plan itself is inherently biased to maximize the metric for which that individual, team, or department is responsible (e.g. a demand plan from a sales-only perspective is likely to call for an increase of certain materials or parts based on the risky perception that enough product will be sold to justify it). By taking the collaborative demand planning approach, all key business departments and functions are heard in the plan and have a say in the output of the work: the Final Consensus Demand Plan that is adjusted for supply constraints.
There Can Be No More Singular “Best Guesses” — Collaboration is the Way Forward
With the point that recent history is now seldom a strong predictor of the future and now even more economic risks seemingly lying in wait in the coming year, manufacturing and distribution organizations would be wise to evaluate their demand planning processes and consider new methods that result in more informed decisions. Collaborative demand planning is essential for an organization to achieve its goal of having the right product in the right place at the right time — and at the lowest cost — with minimal investment to fulfill customer demand and drive profitable revenue growth.
That said, there are a number of key steps that must be followed in order for collaborative demand planning to produce the desired outcomes. In this series, we’ll explore the eight steps of this approach, highlighting the importance of each, what should be considered or included, and how they tee up the following steps. Be sure to check back frequently, as steps will be covered in short order. Also make sure you’re subscribed to our emails so you’re the first to know when content drops.
Until then, feel free to reach out if we can answer any questions regarding your current demand planning practices. Our team is here to help position you for success.
