Everyone enjoys receiving the answer ‘yes’ to all their requests, especially in business. But is it actually possible to hear it all the time, lets say from your boss? You wish, right? But the answer is No. The reason behind it is the trade-off concept which is at the core of almost all business decisions.
Supply Chain is a core business function tasked to manage multiple business operations such as production, inventory, order fulfillment, and transportation simultaneously.
Managing trade-offs between different supply chain functions is a real challenge as each unit tends to operate in a silo and each silo has at least one competing objective with one another. Otherwise, it would have been so easy to ignore the cries of the fulfillment department and reduce inventory by not purchasing a thing and making the inventory guys heroes. Or to reduce transportation costs, it would have been acceptable to order less frequently and build inventory.
Well, the world does not work that way.
In fact, the supply chain people are expected to be super-heroes. They are expected to increase availability while reducing inventory investment, production, and transportation costs at the same time. How can they manage all this simultaneously?
The answer is through concurrent optimization.
Concurrent Planning optimizes orders, inventory, and transport at the same time and in one plan. Rather than sub-optimizing a siloed operation, you optimize the entire enterprise.
Concurrent Planning should not be confused with making plans independently for each function and stitching the results together, as the traditional solutions do.
What if you want to optimize for more than one goal? For example, you might want to optimize your plans to produce the highest profit margin, but also want to minimize transportation costs…It is not realistic to produce a high volume of products to increase production efficiency and have below budget inventory holding costs at the same time. That is why neither the production manager nor the inventory planner can hear ‘Yes’ as an answer to their action plan. Neither of the two functions will want to miss their target KPIs. Here is the question: If each function has its own team planning the operations internally and has its own organizational structure, how can a leader say ‘Yes’ to each function and achieve the best results for the business? There is just one way to get to ‘Yes:’ using advanced analytics and concurrent optimization.
Traditionally, each business function get guidance on its objective and plan their supply chain operations. How does a business perform concurrent optimization? By combining each function’s objectives under one overarching objective and reflecting them on the individual KPIs, the company can uncover solution options that they may never consider. The concurrent supply chains are made possible by high tech software platforms ‘that plan a supply chain using multi-objective discrete optimization technique with goal programming’. Concurrent optimization models enable changing objectives as a dynamic parameter, resulting in a more agile technology that can adjust to the changing business needs. Goal Programming optimizes for more than one goal at a time and constructs solutions by addressing multiple goals for the best overall result. The company follows the market dynamics and adjust their short- and medium-term objectives to have a competitive advantage against their competitors. The company is able to prepare for coordinated actions across its functions.
One top consumer electronics manufacturer which serves its 1,300 retail stores used to have separate functions across several silos for prioritized inventory allocation, credit checks, fulfillment, and transportation planning. Each function maintained its own KPIs to execute its own operations efficiently. This way of working resulted in low fulfillment performance (measured as On Time In Full, or OTIF) and high transportation costs. So, what is the miracle that turned this situation into a success story?
Concurrent planning of prioritized inventory allocation, credit checks, fulfillment and transportation planning combined with scenario planning.
Initially, the company focused on the transportation optimization to minimize delivery cost and increase planning efficiency, resulting in 3.5% savings in transportation cost. It was an improvement with real value, creating a success story and confidence to take on concurrent planning.
As a second phase, prioritized allocation, fulfillment and credit checks are included into the concurrent planning model. Three optimization objectives -maximize sales, maximize margin and minimize transportation cost- are combined under goal programming, while the inventory investment and OTIF targets are met and the whole planning process is automated. On a daily basis, transportation costs are balanced against inventory investment and total margin perfectly by optimization algorithms supported by machine learning. All departments reached and even exceed their KPI target levels over time. The total transportation costs decreased by 18% from base, the inventory investment reduced by 30 million USD and the OTIF targets are met consistently. The daily automated process settled down after a very successful change management effort, convincing each department to work with the new automated process and focus only on the exceptions.
To conclude, concurrent planning is here and real, with demonstrable results. You just need to find your concurrent planning case, say ‘Yes’ to a test-and-learn opportunity, and enjoy the benefits that only concurrent planning can uncover.
In other words, it is easy to say ‘Yes’ to the opportunity to become an immediate hero at your company!!!