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I’ve got bad news for you . . . Well, perhaps not bad news but certainly news that is important.

All that data you have been collecting? Most of it is probably junk.

Those advanced analytical tools? Worthless.

Pretty bold statements, right?

Not really.

In my nearly 30 years in supply chain, I have never seen a system or data that by itself had any value. It was the people who used these that added the value.

Example:

This statement has no value: “This item is 92% in stock.”

So? Is 92% good or bad? For an ongoing item, it might be too low. For a discontinued item it could well be too high, since the goal is to run out of inventory.

OK, smarty-pants, what is your point?

Your data and analytical tools are only as good as the people who use them.

With all the focus on data and analytical tools, I think we are in danger of losing focus on the one element that is key to their successful use:

Tools that are not properly used are worthless and can actually be harmful.

Do not give your 2-year old son a hammer. Just some advice.

Now that I have your attention – and I am sure I have made some of you angry – here are 5 key practices that will make or break your big data and advanced analytical dreams.

1. People will not effectively use data they do not understand

A person who does not understand data probably will not use it well. In fact, they may abuse it to explain away a problem. Someone who does not grasp that your comp sales percentage is negative, or that your in-stock level of 92% is well under the expected level cannot possibly take the right actions to address either problem. And saying, “We’re only 8% out of stock on the item – it can’t be that bad”, is missing the point of using the metric.

2. People need to know how to use and evaluate the data and systems they use

This is largely a matter of education and training. Users need to know that the systems they use have limitations (they all do) and that they are good for some processes and not good for others. For example, does your demand planning system allow for adjusting the history of an item? And does the user understand why this is important and how to do it properly? When do your reports update, and how are key measures (in-stock, lead-time, fill rate, etc.) calculated? Users need the training and tools to be able to evaluate both the tools they use and the data that drives these tools to be able to use them effectively.

3. Users need to trust the data and tools they use

This follows from point # 2 above.

Users who do not understand the data and tools they use cannot properly evaluate and effectively use them. Reports may have bad data and systems may fail to update properly. Users need to be able to spot when a report has errors or a system gives an incorrect output. Some of this comes only with experience, but training users to evaluate and question these is important, since they and others will be using them to make decisions about where to spend company resources – including their own time and energy.

4. Users need to understand how to use the data and tools they are given

This is where training is key, and where many companies suffer because they leave this to chance. The approach is often, “Here’s a manual – figure it out.” Some users can manage learning this way, but many cannot. And while training is expensive and often hard to justify, it amazes me what companies will tolerate as users “learn how to use the systems.” (And in the interest of full disclosure, yes, I have “accidentally” ordered $2M dollars of unneeded inventory. In this business we all get many opportunities to make spectacular errors.)

5. Users need to know how to challenge the validity of the data they use and the value of the systems they manage

To me, this is the goal of all training. When users understand how the tools they use are constructed, can evaluate their usefulness for themselves, trust them, and know how to use them effectively, they can then become effective users of those tools.

And only at this point does all the data you have compiled, and all the fancy systems you purchased start to add significant value to your company.

So the next question is, where are your users in this process of growth?

Your data and analytical tools are only as good as the people who use them.

I know, training is expensive and hard to justify. But this is usually because we don’t calculate the cost of not training our people. We simply live with the cost and inconvenience and call this a “cost of doing business.”

I have personally trained hundreds of users in effectively managing complex replenishment and reporting systems. It’s challenging to try to meet all the levels of ability and understanding in even a small class. But the payback in terms of productivity and the student’s sense of personal accomplishment – while hard to price – is worth all the effort.

And it’s also the only way that any company will get the full value out of the data and systems that they invest in.