When Nothing Really is Something

It’s one thing to look at your ERP system and see information that requires your attention. A purchase order request; a contract that’s about to expire, or an invoice that’s overdue for payment.

But have you ever tried to identify an ERP activity that should have happened – but didn’t? That’s not nearly so easy. Consider a repeat customer who places an order every month, like clockwork. You don’t need an alert when that customer places one of their regular orders with you; rather, you need to know if and when this customer ever fails to place an order with you.

This is a case where the absence of activity is exactly what you need to know.

It’s unfortunate but true that often the most important information for an organization doesn’t concern what has happened, but rather what hasn’t happened. Customers who have not purchased, inventory items that have not been sold, or special offers not taken advantage of are all good examples of business conditions where “inactivity” is key.

Some inactivity scenarios are easier to address than others because they have specific dates associated with them. A service contract (with its expiration date) or a sales order (with its expected delivery date) can be tracked for “inactivity” because their date fields will have not been updated or are in the past. In such cases, it’s not too difficult to run a report or query where your date-sensitive selection criteria retrieves only those records where the “expiration date” is within ‘x’ days, or the “scheduled ship date” is more than ‘y’ days overdue.

The difficulty occurs when there is no such date field associated with an action that should have occurred. A prime example – and a very popular one – is the previously-mentioned “customer who has not ordered” scenario. For some customers, no purchases within the last week is abnormal; other clients may have less frequent buying habits, such as monthly, quarterly, or even yearly.

The problem with this is the absence of data to report on. And the best way to understand this is to imagine a file cabinet. Imagine that you open a drawer and reach for a file called “This Month’s Orders”, filled with copies of invoices. These invoices might show that 60 customers placed orders this month. Unfortunately, these invoices do not help you to see which customers did not place orders during the current month.

So how do you go about reporting on data that just isn’t there?

The answer is “by cross-referencing”.

Cross-referencing is a two-step process, and is typically the only way that “absence of activity” can be identified. In the above example, before you’d reach for the stack of “this month’s invoices”, you’d reach for something else -- a list of all your customers.

You’d pick the first name on the customer list, and then (from the stack of this month’s invoices) you’d count the number of invoices for that customer. Any customer who had zero invoices for the current month would meet your criteria. You’d repeat this process for every customer on your list.

Time-consuming? Yes. Painful? Absolutely. But worth doing? You better believe it.

The problem is that few businesses have the time or resources to do this kind of cross-referencing. But if you can automate this process – much in the same way you might automate sending alerts about overdue invoices and the like – you’ve just gained valuable insight into your business without having to expend significant resources in the process.

Just as today’s alerts systems allow you to configure your ERP solution to automatically tell you when certain critical business activities have happened, you can now use these same alerts systems to tell you about important business activities that have not happened.

It may take a little more effort to configure such “inactivity” alerts as opposed to those alerts that look for the presence of specific data, but when you consider the potential results – the retention of even one customer and their repeat business – the benefits are unmistakable.

Because in the business world, nothing can really turn into something.