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How much is it worth to you? It’s a simple enough question, and it seems it should also have a simple answer. But in a business setting, that’s not always the case.

From an accounting standpoint, defining “worth” is generally pretty straightforward. Though there is an entire industry devoted to asset valuation, it typically is an exercise in purely financial metrics – the market price of a stock, the net present value of future cash flows, the midpoint of a bid/ask spread, etc.

From an economic standpoint, it gets a bit trickier. Take the development of a new condo building – it costs a known amount to develop, and it can be expected to bring in a certain amount of revenue over time. Determining the accounting value of the building is easy, and making a market for buyers and sellers is accordingly straightforward. But what about the economic value? Surely there are more implicit costs associated with the development, like the environmental impact and any impact to surrounding property values. To determine the entire economic cost of such an asset is therefore less clear cut.

For a behavioral economist, the value assessment is murkier still. Regardless of whether costs and benefits are explicit or implicit, their magnitude can change based on your frame of reference. In a well-known experiment, participants randomly given items of equal value were highly unlikely to trade one for the other when given the opportunity to do so. In other words, by merely taking ownership of an item, a participant valued it more than a different item with the same price.

In the business world, what are we to make of this? Decisions often depend on knowing the underlying value of options being considered. How can we determine this value with any confidence?

Recently, a client found themselves in exactly this predicament. They had implemented a solution designed to help their sales team but, a year later, they were unsure of the tool’s return on investment (ROI). The great irony was that the client had foreseen the need to measure how the tool was performing over time and had taken steps to put data capturing capabilities in place that would provide an indicator. However, this data did not provide much insight into what impact the tool was having on actual sales.

The tool in question was designed to help the sales team by automating discounts. The client, an IT distributor, sourced products from a wide array of manufacturers who in turn offered a multitude of discounts and rebates based on attributes like product type, order size, and customer segment. For a sales rep, navigating all these deals to find the best value for a customer could be daunting – and even prohibitive given the short time frames involved with closing some sales.

Implementing a tool that would assess all of the products being offered and then find the best possible discount instantly and automatically sounds like a win for all parties involved, so there was plenty of excitement when the solution went live. And while the client had the foresight to set up a means to track every recommended discount that surfaced, they didn’t know which of those recommendations actually translated to sales, let alone whether the recommendations changed what the sales rep would have done anyway.

Enter Kenway. With knowledge of the client’s business and expertise in Information Insight, Kenway was well positioned to bridge the gap and identify which recommendations led to sales, an analysis which would inform an ROI estimate.

The key challenge entailed understanding how to link recommendations data with sales data. Working iteratively with the client, Kenway leveraged its Business Intelligence service to delve into the data and identify attributes that could link across the two datasets. Using those attributes provided visibility into which recommendations led to sales – a key piece in the ROI puzzle.

Of course, it wasn’t the only piece in the puzzle. As we know, calculating value is difficult. Though it might make the client happy, treating every sale tied to a recommendation as if the recommendation caused the sale would be disingenuous. How many cases were there where the sales rep would have applied the discount anyway?

To determine this, Kenway provided sample data to sales reps to confirm whether the new tool had indeed helped them apply a discount to a sale. In addition, Kenway spoke with key stakeholders on the project to understand which specific recommendations could be ruled out since they were already well known. Folding this information into the analysis allowed for a more informed value estimate that drew upon both quantitative and qualitative data.

So, was it worth it? As our analysis determined, yes.

The solution returned more value than it cost and did so in less than a year. But more important than the binary answer was the methodology behind it. The client had confidence in Kenway’s assessment, because the process used to define value holistically considered the data in context, rather than blindly deriving a number based on the raw sales totals.

Consequently, the client continued to move forward with the tool, and their sales team actually ramped up usage, knowing it would return value.

If you are interested in Kenway’s help determining whether or not it’s “worth it,” visit kenwayconsulting.com/information-insight.