Optimizing Product Mix at Any Utilization Level

Optimizing Product Mix at Any Utilization Level

Traditionally, organizations have seen great divides between production teams and commercial teams. The production teams are focused on the optimization of through puts or simply put, more material in less amount of time. On the other side, the commercial team wants a higher contribution for the volume they are selling. This results in one side pushing for more production per unit-of-time, and the other pushing for more contributions per unit-of-volume. There is a dichotomy here and these siloed performance indicators are often in conflict with one another. Transitioning both groups toward optimizing contributions per unit-of-time should be the goal. How to get there is the challenge! 

Imagine the scenario –the company’s order book is booked solid for this quarter and the foreseeable future. The production leaders are urging their teams to stretch their capabilities to produce all that they can, as fast as they can. The production team is working hard to keep manufacturing humming out of every available hour while lowering their conversion cost. To accomplish this, they cultivate their momentum around the production rallying cry; produce more in less time. In manufacturing, this is typically in units-ofmeasure (UOM) such as pounds per hour, tons per hour, or count per day. Regardless, this UOM typically has volume in the numerator and time in the denominator. This is of the highest importance, because if they make one more per unitof-time, at the same cost, their conversation cost will lower. A win for the production team and typically serves as the bias favorite of their performance indicators.

Under the same set of circumstances, the commercial team is pushing for the most profitable order,while being laser focused on the selling side of the business. The team is taking on the “best orders” while leveraging their business relationships. From their line-of-sight, they are focused on a numerator that is dollar-based while their denominator is volume. Examples consist of dollars per ton, dollars per piece, or dollars per bundle. They are meticulously working their way through contracts and spot business,typically focused on the highest number of contributions per volume. Choosing to take the order at a highest contributions per ton versus the lowest contribution per ton is an easy decision from their perspective

Individually, these two key performance indicators make sense, yet have the tendency to conflict. Most likely, the production team is screaming that certain product mix slows down the production units. 

“Here we go again. Nichole, why do we keep running this hard to produce such slow product!” Then, the commercial team is challenging the notion back that it has the higher contributions. “Look Tony, we make fantastic contributions per pound on this product. It is the highest of our entire portfolio!” This is the dichotomy that stifles the full manufacturing potential not only optimal market conditions, but all market conditions.

This scenario leaves untapped contributions on the table in a fully utilized market condition. While in a non-fully utilized market, it limits maximizing the absolute contributions at lower utilization levels. They might not look like it on the surface, but these are two of the most common conflicting key performance indicators that impact maximizing the profitability of an organization. Instead of solving the conflict, the siloed organization might continue to conduct their portion of the business and march on in their separate ways. As a result, additional contributions garnered from collaboration are left untapped. 

“The Objective Is To Narrow The Evaluation Of The Product Portfolio, Enough To Establish Granularity In Attributes That Are Commercially Offered”

A solution is right in front of both teams. Consider production which is focused on maximizing tons per hour. Then consider a commercial enterprise which strives to maximize the contributions per ton. If we simply multiply these two together, the volume (which is the tons in this example)cancel out. What remains is a contributions per hour. Why not build all strategies to maximize the contributions per hour, and have one key performance indicator for the enterprise, both production and commercial, to rally around? Why not build a collaborative rallying cry in all market conditions, to optimize the business to maximize the contributions per hour?

To solve this within the production side, it is a two-phase approach in most cases. In conjunction with measuring a production unit’s effectiveness, typically measured in Overall Equipment Effectiveness(OEE), the objective is to understand what impacts the bottleneck production unit’s run rates by way of its product portfolio. The objective is to narrow the evaluation of the product portfolio,enough to establish granularity in attributes that are commercially offered. Materialistically, features such as width, length, composition, composition, color, finish, etc. The segregation of the product portfolio should be grouped, yet not so narrow that one does not have enough data to correctly reflect the accuracy and dependability of the run rates. From the commercial side, the contributions per unit-of-volume is now broken down with the same level of granularity as the production team. From here, one will find the product of the two for the applicable groupings of the product portfolio.

Now there is a list of the contributions per unit-of-time, for the desired granularity of the product portfolio. One can now prioritize the product portfolio, while expanding the conversation logically with indirect influencers like customer’s bill of materials, future business opportunities, or product portfolio impacts on OEE availability losses. Visually, a XY scatter plot can be created that has contributions per unitof-volume on the Y-axis, and unit-of-volume per unit-of-time on the X-axis. This provides a simplified product portfolio matrix to align and collaboratively make decisions based upon where the product falls. For example, those in the top left should be prioritized to find ways to drive projects, pushing the data point to the right by being produced faster. Whereas, those on the bottom right, are strategized to push up by either scrutinizing the sales price or reducing the production costs. Regardless, there is now a collaborative performance indicator and a simplified matrix view that the enterprise can rally around

Shifting towards a holistic and non-conflicting performance indicator is not for the faint of heart. It takes confidence, strategy, and intensive communications to get through the barriers of the initial doubters and siloed organizations. Yet when they see the logic, the biggest doubters become the loudest promoters, aligning the entire business to strive in one direction with a single key performance indicator. 

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