Garbage In, Garbage Out: The Importance of Quality S&OP Inputs

By Jonathan Eaton | Vice President, Integrated Demand & Supply Planning Practice

When executed properly, sales and operations planning (S&OP) is a powerful approach that can significantly improve service, reduce inventories, free up working capital, increase available capacity, close gaps to plan, and ultimately drive top-line growth. However, in order to unleash the full value of the S&OP process, many different elements must be brought together in concert to achieve a view that is greater than the sum of its parts. Effective S&OP requires elements commonly examined separately to be viewed in tandem with each other.

inputs-for-quality-sopWith this in mind, the output of the S&OP process is limited by the quality of the inputs. Computer programmers are familiar with the term GIGO – garbage in, garbage out. What comes out is only as good as what goes in, no matter how well designed the program or script may be.

The same applies to S&OP. No matter how well designed and executed the process is, it will only pay full dividends when demand and supply plans are well founded, and those plans utilize quality inputs – because of course GIGO applies to Demand and Supply Planning as well.

Demand Planning

The consensus demand plan is the first major input into the S&OP process.  A strong consensus demand plan requires correctly marrying top-down guidance with a bottoms-up view provided by the demand planner and baseline statistical forecast. As such, this baseline forecast will ultimately set the foundation for the S&OP process to build off of each month. In order to yield an enhanced output, a solid baseline relies on the demand planners ability to manipulate the algorithms within the planning engine and enhance the inputs with market intelligence where appropriate.

To generate a reliable foundation it is imperative to have a good demand planning engine, processes, and planners in place. Before becoming effective participants in the S&OP process, demand planners must fully understand the volatility of their products and portfolio mix. Manually adjusting the forecast for every item is not feasible. A critical facet of effective demand planning requires an understanding of when manual adjustments are needed vs. running on autopilot (or when to let the baseline statistical forecast stand alone).  By first identifying and understanding which SKUs are volatile, this allows the demand planner to manage by exception and focus their limited time on items that truly require their additional attention.

For a deeper dive on how to segment your portfolio and determine where effort is spent best on forecast adjustments, check out my colleague Ben YoKell’s webinar on-demand here.

Supply Planning

Much to the same regard as the demand plan, a consensus supply plan is the other key input into the monthly S&OP process. It takes elements previously considered separately into consideration together such as, safety stock, inventory levels, capacity plans, and alternatives required to meet the consensus demand plan.

When there is significant demand variability, preparing an adequate supply plan to meet forecasted demand can be difficult. Safety stock is often necessary to buffer against unforeseen requirements in order to avoid stock out situations and maintain high customer service levels. However, the amount of safety stock required increases exponentially when the uncertainty in demand and customer service level expectations or commitments rise, and the increase in inventory investment can be significant when service levels are above 95%. Understanding when and where your demand plan may go awry can help with setting appropriate inventory targets, and multi-echelon inventory optimization must be employed to efficiently balance the trade-offs between demand variability, supply variability, replenishment lead times, and customer service.

After agreeing upon what amount might be sold, and how much inventory will be needed to meet those planned and unplanned orders, determining how to produce effectively is the next logical input to take into consideration. Capacity planning is often an underestimated input into an effective S&OP process.  Discussions on how to produce to meet the consensus demand plan should not center on “why we don’t believe the forecast” but rather “what could happen if…” to best prepare the organization. Determining how best to use the available capacity to deliver against the consensus demand plan and then considering alternatives and factoring in tradeoffs for broader consideration is critical.

Putting It All Together

An effective S&OP process can get companies moving like well-oiled machines and enhance visibility downstream and up. Great S&OP execution relies on quality inputs to establish a solid foundation. Once the demand and supply planning inputs are fully vetted and based on facts, it’s much easier to significantly improve service, reduce inventories, free up working capital, increase available capacity, close gaps to plan, and ultimately drive top-line growth.

Clients often come to Chainalytics to request assistance with optimizing or implementing an S&OP process, but we always start with ensuring that a solid demand and supply planning process are in place to assure that the S&OP output is effective and more efficient long term. After all, what comes out is only as good as what goes in.

If your S&OP process feels like you’re spinning your wheels and isn’t producing the benefits you’d expect, take a step back and assess if your demand and supply inputs are ready to produce the quality outputs you’re desiring.

If you need help getting traction, feel free to reach out to me via LinkedIn or continue the discussion on the Supply Chain Intelligence Network™.

Jonathan Eaton is Vice President of the Integrated Demand and Supply Planning practice at Chainalytics. In this role, Jonathan focuses on the delivery of professional services related to S&OP process improvement and implementation, demand-supply balancing, materials management, and inventory optimization.

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