Key performance indicators (KPIs) and metrics are one of the best management tools any company can implement. They can provide actionable insights to improve the operations to drive down costs and inefficiencies.

But there can be a significant downside. That downside is in attempting to compare against “industry standards or benchmarks”. This is not to say it shouldn’t be done, but it should be done with a lot of caution. But we have seen the following scenario play out so many times.

The CEO comes into a meeting and wants to understand why their picking efficiency is so much lower than an industry they read in an article.

The danger is always in trying to get behind this “industry benchmark” and understand the makeup of the data and the companies behind it. Without access to the raw data or even detailed breakdowns or categorizations of company profiles, the results are difficult at best to utilize effectively.

The following 24 points, focused specifically on picking only, highlight why these industry numbers can lead to more wasted energy than they are worth. This is especially true if no underlying data is available. If you can’t answer these within the data provided, be careful not to give these industry numbers too much value within your business.

What was the sample size of companies, and does it accurately represent your business category?
How many companies are using barcoding versus paper picking in a warehouse management system (WMS)?
How many companies are using co-bots to support picking?
How many companies use goods to person technologies for picking automation?
What are the other company’s average lines per order?
What are the other company’s average units per order?
Are any of those companies using pick to light or voice picking?
Which of those companies are picking from pallet versus shelving or carton flow?
How many companies have implemented disciplined slotting routines?
How many companies are discreet order picking versus cart bin picking or other methods?
How many SKUs (i.e. pick locations) does each company have in their pick path?
How many companies are building kits or sets on the fly versus picking pre-built kits?
Which companies are using a pick and pass method or conveyors to move picked orders to packing?
How many companies in the mix are consumer versus business to business?
Who is picking apparel versus appliances or medical devices or supplements?
What size order batches and waves is each company picking?
What level of inspection is each company doing for products picked?
Who must verify lot numbers or expiration dates when picking?
Which companies are capturing a serial number at the time of pick?
Which companies are picking inner packs or cases, but the volume is counted as eaches?
How many companies have a DC where the pick path is physically broken up into different areas?
Which companies have strong leadership versus those who have struggled to attract good talent?
How good are each company’s onboarding and training processes to get new hires up to full efficiency?
Which companies still pick by item number versus location sequence?

So, what do you do? If you have relative confidence in the data behind the benchmarks, use them accordingly. If not, temper expectations internally on utilizing them.

Then, who is the one competitor you should benchmark against? The answer is simple – it’s yourself. It’s benchmarking yourself and understanding your trends over time. In the instance of picking, take your metrics and drive at the following:

What has happened with your average lines and units per order? If the lines and units are up, this will impact the average orders picked per man hour and cost per order.
Has the product mix changed, if the shift is towards smaller items, this should have a positive effect on picking efficiency. Larger heavier items would potentially push your metrics the other way.
Have you added or removed large numbers of SKUs overall? If so, this would have an impact on the pick path, in turn impacting throughput.
Have you implemented additional processes to the pick function that impacts throughput?

Knowing how you trend over time is important. More important is understanding what the number is telling you – and knowing what to do about it. Metrics along with diligently working on warehouse optimization are core components of developing a proactive management approach.

As operations professionals, we must always be working with a continual process improvement mindset.