Usually, a supply plan can’t be fully executed. Robust supply plans can optimize across distribution, manufacturing, and logistics constraints and deliver an optimal plan that hits service objectives at the minimum cost. The integrated business plan is at the heart of balancing projected demand with the capacity needed to meet that demand.
But then stuff happens. There can be surprises that potentially offer a better upside: demand is higher than expected, it is possible to raise prices without affecting demand based on what is happening with competitor products, technology has allowed manufacturing capacity to ramp up faster than expected, etc. But, more commonly there are downside surprises: customers lower the volume they want on an order, delay their order, there are manufacturing problems, logistics problems, staffing issues, to name the most obvious downside risks.
It is better to have an optimized plan than not, but money is left on the table. The worse the disruptions, think COVID, the more money is left on the table. Further, supply chain professionals don’t believe we are going back to the smooth and predictable supply chains of yore.
Now in addition to an integrated business planning process focused on planning in longer term horizons, companies are trying to implement solutions to deal with the short-term upside and downside disruptions. The vocabulary for this concept includes terms like the “Sales & Operations Execution Process,” “optimized execution,” or “holistic control towers.”
Robust control towers that holistically optimize execution are possible. They are just very costly, painful and time consuming to build. In general, to optimize across distribution, manufacturing, and logistics in an execution time frame, companies need to stitch together several solutions. They need supply planning capable of concurrent planning, multi-enterprise supply chain networks, real-time supply chain alerts across an n-tier supply chain, and a data lake.
Concurrent planning is the process of making and managing unified plans across multiple time horizons, business processes and organizational boundaries at the same time. A supply chain solution that understands constraints across multiple domains – inventory, manufacturing, and logistics is capable of optimized execution ASSUMING it has a real-time understanding of what is occurring across an n-tier supply chain.
An “n-tier” supply chain consists of not just a company’s immediate suppliers of materials needed for production, it is the suppliers to the Tier 1 suppliers, then visibility to problems from Tier 2 suppliers that affect the Tier 1 suppliers, and so forth.
Real-time supplier visibility comes from certain vendors of multi-enterprise supply chain collaboration (MSCN) systems. Infor Nexus, One Network, E2open, and SupplyOn have good customer references around visibility to changes at the Tier 1 level and the ability to orchestrate around those issues. These public cloud platforms allow for digital communication between Tier 1 suppliers, the carriers, 3PLs, and a company’s factories and warehouses. If a Tier 1 company is having a problem manufacturing a component for the OEM, or securing transport for a shipment, that is quickly visible. There can be an automated check-off process: will the materials for production on a designated day be there? Automation means the planners don’t have to sort through reams of data to see the problem; the problem surfaces in a user-friendly way.
When it comes to hot items, the trick is to identify what is “news” and what is “noise.” Perhaps a truck is late, but it contains production materials where a company has plenty of stock. On the other hand, an ocean container might come in early but contain products that are in short supply. In that case, the system needs to tell the planner to receive that container first.
Infor Nexus, SupplyOn, One Network and others can look at these exceptions and go in and optimize transport surrounding the problem. But these solutions require going into production planning systems or inventory systems to “optimize” those functional areas. If you are doing optimization in different silos, you are not doing a holistic optimization that maximizes savings.
The n-tier risk problem is solved by sophisticated risk management solutions. You can read about these solutions HERE. And there are very good solutions for real-time transportation visibility that improve the estimated time of arrival. You can read about those HERE.
The Data Lake
So, how do you stitch these different systems together to get optimized execution? You build a data lake that can consume data from the different systems and then feed a concurrent planning application. To do this, IT personnel must generate a harmonized data layer. The critical master data for supply chain management includes sales orders, shipments, inventory, lanes, and manufacturing capacity. Different business systems can define all the fields associated with these forms of master data differently. But the IT group then must take these objects and ask business users what data points they needed for each of these objects. The IT team should not care what various business systems, like SAP, thinks the object looks like. They should care that they have defined an object in a way that helps them solve a critical supply chain problem.
Harmonizing data is a difficult and costly task. Companies need to give themselves plenty of time to work through these issues. For a multinational company, this probably can’t be done in less than a year. Once the data lake is ready, the company can implement concurrent planning. That can also take a year or more to accomplish.
And the Answer is …
So how can this important issue be solved? For optimized execution, the network must run on a common data model, with a single version of the truth, in real time, with the ability to represent multi-party and multi-tier transactions across trading partners.
The first step would be to bring MSCN and concurrent planning together. Pulling real-time visibility into a MSCN in the right way is probably not too difficult. It would be more difficult to pull n-tier risk management data into the model.
No supply chain solution provider has fully cracked this nut. But, Infor Nexus, One Network, and E2open are probably closer than anyone else.