The next generation of digital twins is extending to a brave
new frontier
– Distribution Centers


How companies can take advantage of the vast digital supply chain systems they have at their disposal along with the emergence of fast and more powerful simulation tools.

Digital Twins have been a buzz word for the past few years. Everything from manufacturing to network modeling to city transportation networks has been utilizing digital twins to assist in Modeling, Predictive Analytics, and What-If Analysis. Gartner’s CIO Survey 2020 shows that currently, only 6% of enterprises have implemented digital twins. However, 41% of enterprises expect to deploy digital twins within three years! In the next decade, digital twins will become the dominant design pattern for all digitalFor those who have already begun their journey, digital twins have transformed the ways they plan and execute utilizing data driven analysis instead of guesswork. With the myriad of decisions and choices combined with the pressure of outside forces (faster delivery, labor, technology) the next frontier for digital twins will be the distribution center.For many years, the main usage for digital twins in the distribution center has been by vendors proving ROI for major projects (facility design, material handling, robotics). These digital twins are typically individual events utilized for a specific purpose and maintained by these digital twins also have the limitations of not being validated against real world situations and measured against the actual results. They are what are typically referred to as “Conceptual” Digital Twins. They can simulate a digital twin of the distribution center but is not there for long term usage. Agillitics is working on the next generation of digital twins called Warehouse Optimization Simulation Twins (WOST). These types of digital twins provide long term benefits for distribution centers as they can create an initial digital copy of the distribution center and then be constantly changed to adapt to the real world environment. This can include continuous modeling for changes in the following modeling parameters: These parameters can help determine labor forecasting, resource requirements, new constraints and bottlenecks, and expected throughput. In addition, distribution centers can model the continuous changes to the physical building such as:

  • Layout (Racking Types, Zones, Quantities, Mezzanines/ Expansion Options)
  • Order profiles (% of Single SKU Orders, Units per Order, % of Expedited).
  • Order volumes (Daily, Hourly, Batching)
  • Operational Processes (Picking Methodology, Goods to Man, Sorting and Staging Areas)
  • Automation (Material Handling, Robotics)
  • Product slotting (SKU Location Assignment, Slotting Methodologies, Location Sizes)
  • Workforce (Type, Quantity, Zone Assignments)

The Problem statement evolves into, “How can companies take advantage of the
vast digital supply chain systems they have at their disposal along with the
the emergence of fast and more powerful simulation tools?



In baseline phase, a baseline WOST twin is modeled into the simulation software. The twin consists of the physical building structure (including columns, racking, docks and material handling equipment), operation processes (flow paths, traffic patterns, expected usage) SKU layout-assignment (pick zone, quantity, replenishment zone), vehicles (quantity, type, speed, battery drain) and labor(shifts, quantity, assignment areas, productivity). The baseline can be ascertained by utilizing either actual data from the warehouse (trallers, ASNs, orders) or through expected daily rates and percentages (trailer per day, breakdown of full pallet vs loose case, expected order profiles) based on provided data from thedistribution center.


Once the simulation twin has been baselined and validated, the final phase is scenario building. In this phase, a various number of What-If analysis scenarios can be modeled and the results analyzed against the baseline simulation twin. Scenario results can be stored in the simulation run files or imported from the simulation twin to a data warehouse for long term storage. In either method, scenario results can be visualized through Self-Service Business Intelligence to provide predictive and prescriptive analytics.


In the validation phase, the simulation twin is run over a time period to ensure the baseline results match real-world operations. Two key areas are being validated: first does the simulation capture the real-world baseline operation and second does the output metrics of the simulation match the real world? The baseline operations validation includes items such as bottlenecks, heat maps and throughput, while the output metrics validations include labor metrics such as productivity, utilization, and distance traveled and cost and throughput metrics such as trailers received and shipped, dock to stock time and order lead time.


Agillitics provides different implementation models to Warehouse Optimization Simulation Twins. Agillitics can provide expertise and guidance to companies that want to understand the leading practices around simulation wins or turn-key solutions that model create, test, and deliver a simulation twin in as little as 60 days utilizing best-of-breed commercial simulation and visualization software. Getting started is easy irrespective of your current warehousing technology. For ongoing support, the simulation twin can be transferred over to the internal support team or can be maintained by Agilitics through our G.A.I.N (Grow, Adapt, Improve, Nurture) services offering.