“Garbage in, garbage out”; that’s the typical mantra for simulation and consulting studies as it relates to the quality of the inputs and the resultant quality of the outputs. Having worked with companies small and large, across a variety of industries, we know one thing is true – every bit of detail counts to ensure we can help our customers maximize their operations.

Why? With so many new and exciting automation options available and continuing to develop – robotics, AGVs, AMRs, goods to person systems and more – it can be both exciting and overwhelming to determine which solution best suits your current and future needs. Most importantly, it is crucial to start with the challenge you are trying to resolve; zero in on the data points.

As Abraham Maslow said in 1966, “When all you have is a hammer, everything looks like a nail.” To have an effective solution that allows your company to thrive you can’t throw a “one size fits all” solution in and expect it to work. As an independent automated solutions integration partner, we know just how important it is to pause, review the data points and then review possible technology options and configurations.   

Good Data Drives Good Material Handling System Designs

For a thorough review this means we want, and need, large datasets so we can develop mathematical representations of critical functional areas. Yearly, monthly, daily and hourly data are all reviewed to investigate opportunities that improve both day-to-day operations and the overall “big picture.” To us, data at all levels matters. Certain SKU profiles, rate requirements or business rules can also help determine if one technology option or operational process should be selected over another.

For example, when designing advanced automation, we need to quantify peak historical levels for each major functional area and develop design criteria that will be used as a baseline for sizing. Specific growth targets are then applied to this design criteria to ensure future-proof automation initiatives are developed.

Some crucial details to capture and review:

• Weights and dimensions of products. Without this information, SKUs can cube out or weight out the selected storage container. Nesting and innerpack case quantities can also affect how many SKUs can be stored in an automated system.
• SKU velocity. Knowing which products are fast, medium and slow movers will impact facility layout, storage technology and picking operations. Understanding how seasonality affects inventory is an important factor too.
• Cycle times. Developing a baseline of productivity is the first step in improving it. Are there process or product flow bottlenecks influencing fulfillment rates? Are manual processes inefficient or difficult to complete?
• Operating expenses. Recognizing the impact of labor rates, production costs and service fees on your bottom line can help narrow down where capital and resources should be spent to seek improvement.

Consequences to Poor or Absent Data

In the absence of valid and current assumptions must be made. In some instances, these assumptions may increase the expected system size and push the normal return on investment or payback period beyond a customer’s typical criteria. In other instances, assumptions may undersize a system and not give the full benefit a customer is expecting.

• Inappropriate automation system size, over or undersized
• Miscalculated use of facility space
• Poor technology selection
• Required expansions or modifications, after installation
• Slower or delayed ROI

Material Handling Consulting

Various consulting services look at different warehouse aspects. For example:

• Operations Master Plan – Provides a customized road map to improve your operations through data collection, benchmarking, analysis and actionable recommendations.
• Layout & Warehouse Design – Improves workflows to increase throughput, reduce operator movements and optimize floor space.
• Labor Measurement – Increases productivity and contains or reduces costs with time-centered performance standards.
• Slotting Analysis – Discovers the ideal locations to store inventory to speed up picking, increase order accuracy and reduce ergonomic risks.
• Lean Manufacturing Study – Identifies and eliminates waste within the production environment to increase efficiency.
• Simulation – Mitigates risk and identifies operational opportunities of a new material handling system solution before implementation.

Plan Effectively Before You Integrate

Data analysis is time consuming yet vital. Good customer data is the key to rightsizing automation systems and targeting the proper technology solution. Good data drives good designs. The advanced analysis techniques we utilize help discover the nuances in customer data and decipher the proper recommendation to deliver the best investment.

Our experts are ready to help you find your competitive edge so you can thrive in the future.

Author: Jason Tenorio