February 6, 2015 - 4 minutes read

Nick Spang Time to ROI Case Study

Modern creative firms (marketing, advertising, and PR) face a lot of downward pressure to be lean. Their campaigns have to out-compete other firms in an ever-changing landscape of technology and consumer demand. Because creative firms are extremely expensive and face a lot of competition, they have to constantly prove that they are effective, and so a complex system of collecting and reporting on data has emerged.

The drive for measurement and efficiency has done wonders for Marketing Science, but has also created a situation where marketing analysts end up spending way more time handling the data than actually looking at it, which is where the magic happens. This issue not only dulls creativity but drives down margins on projects.

The financial case for analytical improvements

Companies looking for solutions have a large trove of analytical tools and technologies available but have to deal with decisions like “buy vs. build,” which carry a lot of risk when it comes to big investments like data warehouses, analytical platforms, and predictive models.

Here is a basic reporting scenario for multiple data sources, comparing traditional vs automated data management.
Time to ROI

To analyze data every week analysts have to crunch through manual, repetitive tasks like downloading files, configuring databases or setting up spreadsheets, then copying and pasting excel data and graphs into slide decks. Why go through the pain? Creative firms trying different strategies need deep discovery work in the data – looking at slices across time, brands, and various dimensions to find low hanging fruit or opportunities in a particular channel to do something new that will get their clients the edge or cut what’s not working. And business managers need the reports to know that they are spending wisely.


As firms consider their analytical and reporting options, they must balance their client’s needs for best-in-breed tools with the risk of building infrastructure that ultimately fails to live up to requirements. Lots of firms have been burned by going down rabbit-holes to develop new offerings that don’t pan out but cost a lot of money.

Time-to-ROI provides an easy but robust framework to de-risk projects and deal with choices for where and how to invest in capabilities. The model asks: what is a reasonably quantifiable return and how long to achieve it? The return will generally center on reducing costs and increasing margins. So if analysts are spending 70 percent of their time processing the data and only 30 percent analyzing it, is an investment to automate data processing worth it if it takes 6 months to pay off the upfront costs?

The payoff can also be institutional knowledge, organizational culture, and scalable infrastructure. When that’s the case firms will aim for something south of 100 percent ROI in a given timeframe knowing that there will be collateral benefits. The timeframe becomes critically important here: are you seeing results tomorrow, next month, quarter or year? The more you can quantify what you will produce by when, the more support you can drive through the organization.

Why Time-to-ROI works

Showing Time-to-ROI is a powerful way to gain more support from the business managers that oversee the purse strings. Over time you can see what decisions improve Time-to-ROI for new projects and which ones don’t making it a great indicator in its own right.