7 steps to innovate amid high digital density

How can companies create new value propositions in high-digital-density environments? Jesús Pérez Balaguer, Robert W. Gregory and Javier Zamora propose a seven-step methodology based on the "jobs to be done" theory.

In environments of high digital density, with millions of connected devices generating data, the barriers to entry are lower and new possibilities for innovating open up.

Still, most companies have a hard time spotting such innovation opportunities, let alone systematizing a process to incorporate new ideas into their product portfolio.

Jesús Pérez Balaguer, Robert W. Gregory and IESE's Javier Zamora propose a seven-step methodology to systematize the creation of new value propositions based on the interactions afforded by high digital density.

This methodology is based on Clayton M. Christensen's "jobs to be done" theory, which builds on the premise that customers do not buy products or services, but rather "hire" them to complete certain jobs. In other words, customers don't want products, they want solutions to their problems. This approach starts with the consumers and their circumstances to develop a value proposition that fulfills their needs (an "outside-in" strategy, as opposed to the traditional "inside-out").

Seven steps to satisfy the customer

The new methodology of Javier Zamora, Robert W. Gregory and Jesús Pérez Balaguer comprises seven steps to leverage the vast potential offered by technology in high-digital-density environments. The authors look to a business person hiring a taxi to go to a meeting in order to show how the "jobs to be done" theory works with their methodology.

1. Define the empathy map. The first step is to identify and understand the customer, through personal interviews whenever possible. The goal is to better understand the functional aspects of their preferred product or service, as well as the associated emotional and social aspects. To empathize with this customer, map out what do they think, feel, see, hear, say and do.

2. Identify the job to be done. The prime objective when talking to a customer of a certain product or service is to identify the job the customer wants to be done when hiring said product or service. Find out what their ultimate goal is, the reasons and the circumstances of that need.

Next, state the job simply, using the following syntactic structure: Action (verb) + object of the action (noun) + context. That is, using the taxi example: "Go" + "to a meeting" + "at rush hour."

3. Map out the jobs. Once the main job has been defined, it should be divided into the different tasks or secondary jobs needed to complete it. In the example, that would be: request the taxi, wait for it, travel in it and arrive at the desired location.

It is advisable to use the syntactic structure of the previous point, so the jobs would be defined as "request + the taxi + from the office," "pay + the fee + via credit card," etc.

4. Specify the expected results. This step is about eliminating or reducing pain points and offering improvements. The syntactic structure to use here includes an appropriate metric to evaluate the expected result: "direction of improvement + metric + object of improvement + context." For example, focusing on the wait time for a taxi, the customer's desired result could be defined as "minimize + the minutes + waiting + on the street."

If there are many improvements considered, assign a weight to each based on how important it would be to the customer.

5. Define the interactions. Next, it's time to consider how these expected results could be implemented in a high-digital-density environment, where technology can be leveraged in four types of interactions:

• Automation: eliminate manual tasks to reduce the amount of work to be done and/or the time needed.
• Anticipation: analyze available data to find out the status of any tangible asset in real time in order to describe it, predict its status or prescribe actions for it.
• Coordination: combine different actors in the creation of a value proposition.
• Personalization: adapt a value proposition to the needs of a specific customer.

In the taxi example, the expected result mentioned above (minimize + the minutes + waiting + on the street) could be implemented thanks to various interactions: calculate the distance between the customer and the taxi driver based on the real-time information automatically provided by their mobile devices (automation); integrate the functionalities of an application such as Waze to predict the arrival time (anticipation); add the services of a platform like Uber to locate the nearest driver and minimize wait time (coordination). For another expected result, customers could be offered their favorite music during the trip by linking their Uber and Spotify profiles (personalization).

6. Identify the key actors and data needed. After defining the digital interactions involved, the next step is to identify which actors are necessary to carry them out, what type of data is needed from each of them and how to go about obtaining said data. In the taxi example, the actors would be the passenger, driver, Waze, Uber and Spotify. The data would come from user profiles in the apps.

7. Implement the products or services. It's not necessary to offer all expected results in the first version of a product or service. Since, in digital environments, technology makes it relatively easy to reach customers, measure how they use a product and receive feedback, experts recommend launching a prototype or MVP to test it, adapt it and improve it in successive versions.

Here, in this final step, it is highly advisable to rely on some of the typical methodologies of innovation processes — namely, Design Thinking, Lean Startup and Agile methodologies.