Some suppliers of supply chain planning (SCP) software are experiencing robust growth despite the global pandemic. Solvoyo expects to grow by 15% this year. Kinaxis, a public company, reports that their revenues over the first 3 quarters are up year over year by over 25%. RELEX Solutions expects their revenues to be up by about 30% by year end despite the company’s decision to deemphasize growth and become more profitable. Adexa expects that their revenues will grow by 35% or more by the end of the calendar year.
For each company, there are more than one reason for the robust growth, but all make the point that the need for an agile supply chain has never been stronger. Dramatic demand shocks have been all but impossible to forecast. Agility is what is required to respond effectively when supply chains are being whiplashed in unexpected ways.
Global supply chains have changed more in the last six months than they have in the last six years according to John Sicard, the CEO of Kinaxis. “Never has supply chain management been more important.” Despite being a supplier of SCP software, Mr. Sicard argues that “techniques matter more than technology. We have spent the last decade focused on the ‘perfect plan.’” Many companies have a metric that measures plan accuracy and these companies work, for example, to move plan accuracy from 75% to 78%. “Where is the breakthrough in that? Accuracy in planning is crucial. But equally important is agility. Legacy techniques focused on the perfect plan makes achieving agility tougher. Agility has atrophied.”
What does it take for SCP to provide agility? Supply chain planning vendors such as Solvoyo, Kinaxis, Blue Yonder, Adexa, and OMP speak how concurrent planning is critical for agile execution. Concurrent planning links execution plans, the plan for what will be made the next few days or weeks, to the longer-term integrated business plan. Integrated business planning (IBP) matches projected demand to what a company can feasibly make over the coming months. As new short-term plans are created, the linkage to the revenue and profitability goals based on the initial IBP plan becomes instantly visible. Whereas IBP plans are typically created once a month, agile companies adjust their supply chain plans on a daily or weekly basis based on what is occurring in the external environment.
According to Cyrus Hadavi, the CEO of Adexa, the key to concurrency (which Adexa calls “event driven planning”) is a unitary model of the extended supply chain, both horizontal and vertical. Historically, a supply model – increasingly referred to as a “supply chain digital twin” – was limited by computer processing power. Thus, companies might deploy a higher-level model for IBP, but then would need a much more detailed model to optimize factory scheduling. When the factory was told to produce a certain number of items on a certain day, they could not do it.
This is because the higher-level plan did not fully understand the factory’s constraints. The higher-level model might show that a factory line could produce 1,000 items in an hour. However, this number can change drastically depending on the product mix. Execution solutions would understand the impact of product mix and other constraints. Further, the model would understand how that set-up time could change based on the routing of the product, and whether the setup time changes if product A is made after product B versus being made after product C.
In short, many existing IBP models are sufficiently horizontal – they model constraints across an extended supply chain that includes suppliers, transportation lanes, distribution constraints, and the factories. But these models were insufficiently vertical, particularly when it came to modeling the actual constraints of the operation.
When it comes to digital twins of the supply chain, the retail supply chain has not traditionally had robust vertical modeling. That is changing. Johanna Småros, the Cofounder at RELEX Solutions, described their new capacity solution to me. RELEX Solutions is focused on serving retailers. The solution starts with an unconstrained forecast across all channels. The solution translates that into inventory requirements and how those goods need to move through the supply chain. Constraints include things like: how many order lines need to be picked for a particular store, how many pallets can fit on a truck that delivers to the store, the ability to ship goods that reside in the same aisle in the same shipment, whether goods will be stored in the back room or on the shelf (and the storage capacity of both), product expiration dates, store labor constraints in receiving and putting goods away, and other things as well.
This modeling supports store agility by allowing product deliveries to be pulled forward when this can be done without other negative consequences. Goods are pulled forward to level out the flow of goods, to maintain enough safety stock to ensure on-shelf availability, or to maintain a visual minimum to ensure that product displays look attractive. As omnichannel fulfillment flows increasingly include the store in different types of ways, these flows and safety stocks also need to be modeled.
How do you know if a model is sufficiently granular? Mr. Hadavi of Adexa says that they tell their prospects that they can create a model that will allow their customers to generate plans that can be successfully executed 98% or more of the time. By that he means that in the absence of any surprises, that original plan can be reliably executed without any manual adjustments. High level IBP plans are not executable without planners’ intervention.
But it is not just about the ability to create one, very granular digital twin based on a consistent data model. As Omer Bakkalbasi, the Chief Innovation Officer at Solvoyo points out, to be able to build a good digital twin you need “to represent the supply chain at the highest resolution and have the ability to keep the representation current as the world changes.”
Mr. Hadavi told me that it is natural to keep the horizontal model up to date. For example, as new products are introduced, the routings and set up times need to be put in the model. But continuous improvement in planning would suggest that over time the vertical model needs to be enhanced as well. Over time, the model should get deeper and more accurate.
In terms of driving agility, the SCP solution also needs to understand when changes in the external environment demand that a plan be rerun and when the existing plan is fine despite changes to the environment. In short thresholds need to be defined, once an event passes a threshold the planner understands that they must act. For example, if components for a supplier will arrive late, but demand has softened, no change needs to be made. But if key customers orders will be late because of a delayed inbound shipment, the planner needs to figure out how to correct that situation. When companies begin their SCP journey, the thresholds are often too tight, and the plans become too “nervous.”
In short, growth in the SCP market is occurring not despite the COVID-19, but because of it. SCP suppliers who can support concurrent planning are doing just fine.