How can a long-established organization find new ways to grow and increase its relevance? That was the challenge we faced at APQC (formerly American Productivity and Quality Center), a nonprofit with more than 500 members that focuses on benchmarking, performance improvement, and knowledge management.

While we had no shortage of ideas, we wanted to be sure that APQC advanced in the right direction. The organization needed a compass for long-term priorities, based on what members wanted, whether or not they thought of APQC as the go-to for those offerings.

In the lingo of business schools, we wanted to understand our members' "jobs to be done," so that we could go beyond one-off requests and temporary solutions to find what people really needed to accomplish. The leadership team was conscious of the words of Henry Ford: "If I'd asked people what they wanted, they would have said a faster horse." We aspired to more.

We choose an approach called the Jobs Atlas, which is explored in depth in the book Jobs to Be Done: A Roadmap for Customer-Centered Innovation, to achieve these aims. The process was meticulous and rigorous, taking place over the course of three-plus months. However, it's also a concept that other organizations, including associations, can apply. Essentially, the Jobs Atlas provides a blueprint for how to serve members, enabling the organization to focus on key growth areas while adjusting existing services and messaging.

A key insight from the approach was that demand is not one-dimensional. It's not just about what services people would appreciate, but the context in which those services might fit. The Jobs Atlas shows organizations where they can gain traction, and we built it using three critical steps.

Step 1: Know Where to Start

Constructing the Jobs Atlas began with an understanding of what members were trying to accomplish, regardless of what APQC was doing. For instance, staff at member companies were facing a flood of data and metrics. They needed help making this information actionable.

First, we looked at "job drivers," or the forces that lead people to prioritize different jobs. These jobs varied if people were setting up a new function, trying to validate a position, or seeking to fix a known problem.

We also looked at current approaches and pain points associated with getting jobs done. In the case of data overload, we examined the ways in which data was being used by people who managed a line of business day-to-day. We found that approaches varied, from the very limited to the extensive and sometimes oversophisticated reporting that emanated from analytics departments. We saw that there were distinct levels of development among members, enabling an organization like APQC to codify and share best practices.

Step 2: Chart the Destination and Roadblocks

We then moved to examine what a solution should achieve. An example is that information on peers' approaches had to be searchable and provide detailed models to emulate. We also looked at obstacles to adopting new solutions, such as the time it took to learn new tools and concerns about whether approaches were sensitive to the context of particular industries.

Step 3: Make the Trip Worthwhile

By taking a step back to understand what members needed, we saw what was missing. In the case of data analytics, we were reminded of a quote by famed management writer Peter Drucker: "The customer rarely buys what the company thinks it sells him." APQC's members were contracting with IT research organizations, and they received all kinds of information on how to collect and process data. But, what they really needed were ways to build buy-in to the data and use it day-to-day. By understanding the jobs that people truly prioritized, we figured out the value of a solution.

Ideas into Actions

Armed with the insights and priorities established by the Jobs Atlas, we could then develop solutions tied directly to market insights. An internal task force assessed the project outputs, ensuring that ideas were evaluated based on real needs rather than preconceptions or politics. As a result, two major areas were pursued and subsequently launched. The first provides perspectives on big data to non-analytics professionals within the supply chain or finance fields. The second is a peer-to-peer benchmarking exchange about how to create a data-driven culture.

Drucker's quote from about 50 years ago still holds true today. But it can be difficult to get organizations to step back and learn more about their members' perspectives in order to get actionable results. This process provides a route to make that happen.