10 Ways to Improve Your Internal Benchmarking Programs

One of the most important pieces to managing your operations is to understand how your workers are performing, how costs are trending, and what to do based on what the data is saying. For companies that are just beginning to implement metrics and KPIs, the task can seem daunting. For companies that have utilized benchmarking for quite some time, they might have benchmarking that needs to be reviewed and evaluated. Consider these 10 aspects to improve your internal benchmarking programs.

1. Tracking Employee Productivity

The only way to improve your warehousing and distribution operations, as well as to prove to management that you are operating as efficiently as possible, is to understand exactly how productive your workers are.

FCBCO will soon be launching a new benchmarking program for consumer brands,  to be notified follow this link to let us know. 

Most warehouse management systems (WMS) can assist with tracking worker productivity through various functions such as receiving, putaway, picking, packing, and shipping. Without a WMS, companies must track this information manually. While it may not be ideal to manage this information outside of a system, it is critical to ensure that you are maximizing every labor hour.

The critical first step is to begin capturing the data and understanding worker throughput rates across different functional areas. Companies can download our workbook on critical KPIs and calculations.


2. Establish Productivity Goals & Targets

Once you have begun to capture throughput rates, the next step is to set targets or goals for each functional area or department. Benchmarking programs ensure that employees are working to a standard or goal instead of just working to the workload.

If your order profiles are common across all orders in picking, tracking on a lines or units per man hour basis could work very well. On the flip side, if you have a wide range of order profiles with no commonality, it can be unfair to some employees to track on just lines or units. For example, a single line single unit order is easier and faster to pick than a 20-unit single line order.

Avoid presenting all work at once to the employees. Over time they will get smart to what work inflates their numbers the most, and cherry pick those from the others. This is that last thing you want, float the work out in small batches, or assign specifically to employees if your system can support that.

Also avoid taking the top performer and saying that their work is the baseline. It should be an average working speed that we are expecting from the employees. You also will not know a baseline after one day. You need to understand your metrics for a month minimum before you start making baseline assumptions.


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3. Provide Timely Feedback Regarding Productivity Data

Feedback to the employee and department managers is key, you must empower these individuals with implementing management expectations from a labor perspective.   It is not enough to just post reports in breakrooms or on whiteboards.

Management and supervisors must have access to this data daily and integrate it into their meetings with each shift. Focus on the important pieces – how is the department or shift performing, are they meeting the goals or targets, positive reinforcement – especially to those workers that have greatly improved, etc. It is also important to call out where productivity is slipping, and to reinforce this with the workers.


4. Be Sure to Discuss the Importance of Productivity Metrics with Workers

To be effective, workers must understand why you are collecting information and why it is important to the company. If you fail to help them understand this, or reinforce its importance, you will not be successful as workers will generally not find it to be a top priority.

This is magnified if you are planning to attach workers pay to any type of productivity measures. It must be easy to understand by all employees and must be fair to both them and the company.


5. Understand What the Numbers Are Telling You

Many companies collect and report productivity data without truly analyzing the numbers or understanding what should be done. It is important to remember that these metrics are indicators to relative performance. If that performance begins to go in the wrong direction, you must first identify the trend and then understand what to do about it.  

As an example, if picking productivity is declining, it is important to quickly diagnose the problem and set a direction for corrective actions, including:

  • Is the decline due to insufficient product slotting, slowing down pickers?
  • How has the product mix changed over time, are pickers having to pick larger, heavier items?
  • Are value added services now having to be performed in picking such as tagging items or repackaging at the time of picking?
  • Has there been employee turnover that has negatively affected the overall throughput?

6. Don’t Take Someone Else’s Metrics and Make Them Yours

A major mistake is to see the metrics of a comparable business and decide to implement their throughput or productivity rates. The risk is in what you don’t know:

  • Are their lines and units per order the same as yours?
  • Do you both have value added services, or are you different?
  • Are their systems better than yours at managing the workload?
  • Do they utilize automation that makes it almost impossible for you to match their capabilities?

It is far more important to measure yourself internally and understand your relative performance over time. Outside metrics can provide value, just be sure to understand how the numbers were derived, understand if they are truly comparable to you, and how they should influence your program – if at all.


7. Throughput Doesn’t Mean Anything Without Accuracy

This is one of the most important pieces to keep in mind. An employee, team, or shift that meets or exceeds the productivity and throughput goals is meaningless if there is no accuracy in the work they are performing. Many companies fail to report accuracy along with throughput in their metrics, allowing workers to continue without understanding how they are costing the company and impacting customers.  By focusing on how to reduce picking errors for example, will assist with improving overall metrics. 

It is not uncommon to eliminate workers from productivity incentives if their accuracy is poor.


8. Know Why You Are Benchmarking

Some companies just begin tracking metrics because a system is capable of it without understanding what is being tracked, why it is being tracked, or what the metric is telling you. Companies need to agree on what will be measured, how the information will be used, and what determines whether a particular trend is positive or negative. This information should then be conveyed to the workers so that everyone understands. If you are just capturing metrics with no plan on how they will be used, etc. then the data being captured and presented is irrelevant in your operations.


9. Don’t Get Overwhelmed by Trying to Measure Everything

When starting out, the desire is to launch a program measuring everything that a company can get their hands on. Companies should prioritize metrics based on the biggest challenges, or the biggest opportunity for improvement within the operations. The data for other metrics and KPIs should be captured for future use.

For many, this is picking. Capture metrics on picking and then once that is underway and working smoothly, add in the next biggest functional area.


10. Don’t Solely Focus on Productivity Metrics

Cost based metrics are just as critical as worker productivity, the problem is that most WMS solutions only focus on worker productivity. Measure and report on cost-based metrics such as the total warehouse costs as a percent to net sales and the total cost per order and shipment. Other important metrics include the cost per unit for various warehouse functions like the cost per unit received, picked, kitted, or assembled. These cost-based measures will help you understand where to reduce waste and excess handling.

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