Warehouse Management Tips — Metric Mistakes to Avoid

When you read articles on warehouse management tips, you’ll find plenty on how to arrange items for maximum productivity, pick/pack systems, helpful tips for ensuring thorough inventory, and other useful tips.

But what about warehouse metrics? Of course, your company collects metrics on inventory, warehouse management, and shipping.

But what if your company is making decisions based on mistaken ideas about warehouse metrics? You could be missing significant opportunities, or worse still, making decisions based on faulty assumptions.

Warehouse Management Tips You Won’t Hear Anywhere Else

Very few of us were trained in data analysis. Many people cannot read graphs and charts well. Others simply make mistakes when looking at business metrics.

Yet, business owners are constantly urged to manage by the metrics, to make better business decisions based on data … the list goes on and on.

No one wants to confront the elephant in the room: we may be looking at metrics all wrong.

Ready to develop an action plan to tackle warehouse management metrics? We have a new e-book you can download to help you fine-tune your distribution metrics plan. Download your copy of Distribution Metrics that Matter today.

Common Metrics Mistakes

The most common mistakes that businesspeople make when looking at data include:

1. Lack of strategic alignment
2. Lagging versus leading indicators
3. Missing benchmarks

Lack of Strategic Alignment

One of the most common metrics mistakes is a misalignment between KPIs or objectives and the metrics themselves.

The first question you should always ask before collecting data is, “What is the goal?” What will you do with the data that you collect? By itself, data isn’t very useful. It’s only when it is used to measure progress against goals and key performance indicators (KPIs) that it can be considered useful.

Many companies embark on their digital transformation and add excellent ERP platforms to their companies, only to fail to receive the full ROI benefit of the technology because they did not align their data collection process to the goals.

The key is to understand what drives business outcomes – what will improve profitability, efficiency, margins, and service. Then, assign metrics and goals to each major area. Finally, you can examine the data that supports each of these goals and find ways to capture it. In this way, data collection and metrics will be aligned with the goals most valuable to your company and its success.

Lagging vs. Leading Indicators

Manufacturers seem to focus on leading indicators, or signs of what might be occurring in the macro and microenvironment that can affect sales and profits in the future. But ignoring lagging indicators can be to your company’s detriment. As the name suggests, lagging indicators are metrics of what happened in the past. And, in the past lies clues to the future. Consider both sets of data for the complete picture and then make decisions based on all available data, not a subset.

Missing Benchmarks

Companies are often so focused on their own activities that they fail to consider the fact that customers see many companies’ activities. As a result, distributors can miss important industry benchmarks by only looking inward.

The flip side of this is the company that only looks outward, chasing after a competitor’s every move. Such companies become pale shadows of the competition and fail to improve based on their own merits, always seeking to be like the other brand. And they can never be as good or better than the competitor, because they are always one step behind the competition.

The solution is to find a happy medium between only looking inwards and chasing after what the competition is doing. The gap between the two are internal benchmarks. Failing to set these benchmarks opens the doorway to chasing the competition and other mistakes.

By examining past data within the ERP system, you can find, set, and manage benchmarks important to your company’s success. Then you’ll have your own goals by which to judge success or failure, and there will be no need to chase the competition.

The Biggest Mistake of All: Poor Quality Data

We’ve placed this one in a category all its own because of its important. If you begin your metrics journey with poor quality data, you’ll get lost on the way.

Poor quality data is either inaccurate, incomplete, or both. In some industries, inaccurate data provides a completely misleading picture. If your company is still conducting inventory using staff to count and mark products on a piece of paper on a clipboard, chances are good you have inaccurate inventory data in your system. Manual data entry often introduces data errors that are difficult to find and rectify. Similarly, poor procedures in warehouse and shipping areas can also lead to inaccurate inventory data. Failing to track fixed assets, reconcile bank statements and credit card statements, uncollected invoices and other delays can also lead to inaccurate data.

Incomplete data often occurs when only a partial data set is collected from a situation. Perhaps a customer record is only partially completed, and the phone number is missing from the form field in the ERP. The result is an incomplete record.

When either inaccurate or incomplete data is used to generate reports, the resulting reports will show flawed data. Interpreting such flawed data as accurate can lead to misjudgments that can cost companies a great deal of lost time, productivity, and revenue.

Fixing Bad Data for Good Metrics

Ensuring that your data is clean and error-free is the first step to ensuring good quality metrics. If you’re just starting to transition to an ERP platform, you’ve probably heard the term “data dictionary” in meetings. A data dictionary is a rulebook for what kinds and types of data are collected in the database and the rules surrounding updating the data. It’s a good idea to revisit your existing data dictionary if your company has already implemented an ERP to ensure that the rules are fresh and top of mind among the people who are entering data.

Cleaning data is an art. Updating address files, suppressing records of companies which are no longer in business, and determine which is the preferred record when two records exist for the same company takes time and effort. There are third-party companies that can perform basic mailing list hygiene, such as updating address files, and other companies that specialize in updating databases. It may be worthwhile to investigate their services if you find your data is faulty.

Good data equals good metrics. Preventing common database mistakes and ensuring clean data will help you gain the insights you need from your ERP system to enhance profitability.

 Warehouse Management Tips from Mindover Software

Mindover Software works with distributors and manufacturers to optimize their warehouse management. We can help you get clean data and choose the right metrics for your operations. Don’t forget to download our free e-Book, Distribution Metrics that Matter. And contact us to get started toward greater efficiency and profitability.