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Democratising Strategic Planning with Simulation

Craig Sears-Black
Operating Partner at EmergeVest
Non Executive Chairman at Atheon Analytics Ltd
NXD at detected Ltd

Having worked in supply chain technology since 1998, I have often wondered why we are still so reliant on complex spreadsheets for planning strategic change. Very little has changed in this regard over the last 26 years. Whether in transport, sourcing, or warehousing, the picture is the same: many great operational tools have been successfully deployed, but strategic planning tools are still in the minority among supply chain operators. I believe Kallikor has the opportunity to transform the way change to a physical supply chain is planned.

As we are all aware, the magnitude of change, the pace of change, and the options available to us have increased substantially in such a short time. In the warehouse, robotics and automation capabilities enable an array of opportunities to increase productivity; however, there is a lack of expertise in comparing new options to traditional solutions. It becomes an easy route just to upgrade existing automation in the warehouse rather than change it for a solution that could create significant improvement in throughput or flexibility. Similarly, using robotics to replace manual processes has risks and uncertainties that can be difficult to evaluate when moving beyond a small-scale POC to a full multi-DC rollout.

I have found that on many occasions, speed is everything; the time taken to brief an analyst on a situation and possible solutions, then have them go away and come back with answers 2-3 weeks later, is just not good enough when dealing with major incidents and disruption. My experience tells me that strategic planning tools are far more powerful in the hands of supply chain operators, enabling fast, iterative, and team-based solutioning.

The Adaption platform that Kallikor brings to market addresses the weaknesses of existing simulation tools by simplifying the creation of synthetic representations of the real world. Adaption goes beyond traditional digital twins, offering dynamic, real-time simulations that don’t just react to the present but anticipate the future. Supply chain teams collaboratively run experiments on those models to create KPI outputs, enabling relatively simple comparison. This has the potential to expand beyond a single element of the supply chain, such as the warehouse, to ‘whole supply chains’ linking inbound, national distribution, regional distribution through store distribution to customers.

The tech behind the solution has been put to the test in some of the most complex ‘whole world’ scenarios in supply chain and other physical infrastructure environments. Now it is being packaged to put power into the operator’s hands. The initial focus on the inside of the warehouse enables rapid evaluation of strategic options, with ‘experiments’ being created and run in minutes. This is a game-changer in strategic planning, opening up the opportunity to run, for example, ‘cost to serve’ scenarios by changing multiple infrastructural, volume, or time-based parameters to model profitability at a highly granular level.

Simulation is not new, but it has been confined to specialist tech functions that can spend months creating digital twins of a physical system. Once created, the complexity of the model usually means it is not updated with changes and, therefore, becomes obsolete very quickly. Ease of use, accessibility, and simplicity are needed to put these tools into the hands of people who can use them to effect change.