Transforming Operations with Advanced Analytics
If you have been to any trade shows in the past decade, you have been inundated with the number of solutions you can implement in your Warehouse. From robots to digital twins, there is a plethora of possibilities that could take your warehouse operations into the 21st century. However, deciding where to start and which options can provide a guaranteed ROI can be extremely difficult.
When managing a Warehouse, we have seen a path that can help companies innovate straightforwardly and with a proven ROI. This Analytics Maturity Path is like what we suggested in a blog on Manufacturing Analytics. It comprises five steps that build on each other to ensure operational efficiency across your operations.
Data: Have you already digitalized your main processes? Are you still capturing data in Excel Sheets?
Descriptive: Do you understand what has happened and what is happening? Do you have automated metrics and reports driving your operations?
Diagnostic: Do you understand the main driving forces behind your performance?
Predictive: Do you have a way of estimating what will happen in the future?
Prescriptive: How are you simulating and optimizing future scenarios?
Analytics Maturity Path
This path could be implemented in multiple ways to meet your particular needs. The following are different projects that Ventagium has implemented with our clients for each step of the Analytics Maturity Path.
First Step: Data
The first step in every analytics endeavor is Data, which we can translate into getting the right data in the right place at the right time. For us, this means two main lines of work.
Digital Transformation: Across Supply Chains, it is still common to see operations run on Excel Sheets and printed sheets. With the help of low-code tools, it is now possible to revolutionize these processes quickly and guarantee the robustness of your day-to-day operations.
Data Engineering: Across industries, it is commonplace for companies to have multiple systems that power their Warehouses. Some examples include WMSs, TMSs, ERPs, HR Systems, LMSs, CRMs, etc. Getting all that data in one place is critical to creating a 360° pulse to ensure that we can control our operations.
Second Step: Actionable Insights
The second step is to start visualizing all that data in ways that drive actionable insights through Descriptive and Diagnostic Analytics. This step is when you can start automating all reports done manually across functionalities to ensure Supply Chain Professionals go from managing Excel Sheets to managing their Supply Chains. Some examples for Warehousing include:
Order Management: Managing hundreds of Work Orders at a time can be a massive challenge if you don't have the right tools that trigger your people to act as much as possible to deliver within the expected contract agreements. There are multiple ways in which Orders can be visualized to ensure you are acting fast. Some examples are Process Behavior Charts, Bullet Charts, Process Mining Charts, Sankey Diagrams, and Action Centers. You can see some examples here and here.
Aging Inventory Tracking: If you are managing Materials, Components, or Customers' finished Goods for clients, you must have visibility into how long each of your SKUs has been sitting in your Warehouse.
Cycle Counting: gone are the days when you could shut down your operations for a full day to do a physical inventory to adjust your inventory management system. Cycle counts can be done continuously to ensure high inventory accuracy, driving better operational planning and accounting benefits. Analytics can help you in two ways. The first is driving this cycle count by determining your cycle counting frequency. The second is determining which SKUs should be considered through a predictive Pareto analysis of commonly used items.
Customer Profitability: determining your accounts' profitability requires a profound understanding of revenue and cost. Revenue is easy to calculate, but understanding all cost levers can be tricky if you don't have all the necessary data. By integrating disparate data from functional areas such as logistics, accounting, and human resources, we can understand which customers drive profit across each process, product, or service.
2-D and 3-D Visualization: Mapping locations across your Warehouse space can be crucial to identifying areas for improvement. Take a look at this blog post with an interactive example of how inventory can be visualized to identify potential empty spaces in warehouses.
Process Mining: Certain repetitive processes, such as picking and placing, can benefit from an area in Analytics called Process Mining, which provides transparency for each activity in a process. A clear understanding of how much time each activity takes in your Warehouse drives Continuous Improvement and Compliance. Take a look at some examples here.
Third Step: Predictive Analytics
The third step is when we stop worrying about what has happened and transition our attention to what will happen through the power of Predictive Analytics. Here are some examples:
Labor Forecasting: when we truly understand the main drivers behind our demand, we can start predicting how much demand we will have over the coming weeks and months. This, coupled with a thorough understanding of how many people are needed to tackle that demand, is the key to estimating how many people we will need to match demand.
Capacity Planning: Similar to the previous example, having a clear picture of demand for all SKUs allows you to ensure enough rack space to accommodate all your small, large, and bulky items across your warehouses.
Fourth Step: Anticipate
The fourth and final step is to be able to anticipate multiple scenarios. Being able to re-create tens of "what-if" scenarios is something that would not have been possible some decades ago. But this is now a reality for organizations that have gone through the previous steps. Knowing what may happen and what to do is critical to running any Supply Chain. This concept is also commonly called a Digital Twin for a Warehouse. Here are some examples of how this could be applied:
Simulation: Various techniques, such as Discrete Event Simulation, allow you to test changes in layout, workforce allocation, and equipment utilization without disrupting actual operations. You can determine the most efficient picking routes, assess the effects of adding new storage systems, or predict how peak season demand will affect throughput. By providing a virtual environment to experiment with different approaches, simulation helps warehouse managers make data-driven decisions that enhance efficiency, reduce costs, and improve overall service levels.
Optimization: Using various mathematical models and algorithms, you can optimize storage space, manage inventory, and pick strategies. By identifying the most efficient ways to allocate resources, route workers, and utilize equipment, optimization helps minimize costs and maximize productivity. For example, it can determine the optimal layout for storage racks to reduce travel time, calculate the best replenishment schedules to avoid stockouts, and develop picking plans that reduce order fulfillment time.
Evaluating potential solutions in the market is overwhelming, but with a framework like the Analytics Maturity Path, you can ensure a straightforward approach to taking your Warehouse to the 21st century. It is not easy, but time and time again, we have seen how clients benefit from each step of the journey. Whether visualizing order management, optimizing inventory tracking, or leveraging advanced simulation and optimization techniques, each step builds on the last, providing a proven path to guaranteed ROI.
At Ventagium, we've successfully implemented these strategies for our clients, helping them transform their warehouse operations into streamlined, data-driven powerhouses.
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