Carlos Oliveira

@colivetree

The Job Canvas — Rallying around the Job To Be Done

A tool to maximise learning when going from customer motivations to execution. A simple canvas to visualize your team’s work to discover, execute and integrate around the job to be done.

The call of progress

The Job Canvas starts from the Job To Be Done. It assumes you have talked to customers, collected insights from the data at hand and explored the dimensions of the problem you’re trying to solve — and then summarized it in the Job To Be Done format. I’ve typically gone for Alan Klement’s proposal and chosen <Situation> <Motivation> <Expected Outcome> as the cornerstones of my Job Story. This short format can encompass known trajectory (with situation), pain points (with motivation) and rightly focuses on outcomes (vs outputs).

So what does the Job Canvas do?

You would hire the Job Canvas to help your team outline the key steps and measures you’re using create a solution that can itself be used for the job you’ve identified. These define the state of what you know in the context of what we are building — there should be other competitors out there, even outside our product category, competing to solve that same JTBD, so this applies specifically to how you’re thinking of solving it.

The Job Canvas template

So starting from the top-left, you find:

Insights

What do we know about the problem, do we have quantitative or qualitative data, have we talked to users, are there complaints we’ve received or customer support nightmares, interviews we’ve made, surveys we’ve ran?

Hypotheses

What are our assumptions underpinning a potential solution. If a customer is looking for something chunky to fool her stomach during the morning commute, that could be a Protein Bar, a sack of peanuts, a milkshake, a piece of fruit or even a magazine or a game that takes their minds off of food until they reach the office. We can hypothesise that certain features of our solution will get the job done.

Success

What happens if we achieve the impact we’ve defined? This should typically be quantifiable. Activation rate is up. NPS is up. Failed searches are down. Customers buy more, complaints go down. Define your Overall Evaluation Criteria upfront and only change it if the problem/job does as well.

User Experience

It helps to have a clear picture of what your belief is “today” of how you’re going to solve that job. It could be a rough mock or a high-fidelity prototype, depending on where you are in the Product Development lifecycle. It should change over time as you discover, but it describes the type of end game you are visualizing, so your team has a common understanding of what they’re iterating on (or towards).

Experiments

Finally, I’ve designed the Job Board to make progress by means of experimentation. Anyone that has developed anything for people knows that product development isn’t linear. We learn as we go. Melissa Perri refers to this process as the Product Kata, but there are multiple experiment-driven approaches to product development. Bear in mind that this doesn’t necessarily have to include a controlled (AB..n) test, although that is a natural candidate for this job. This section is where you’ll describe what you’re doing to prove/disprove your hypotheses. Using a description like that in the Hypothesis Kit is very useful and gives you the consistency you likely need.

Working through the problem space

Product Managers are awfully aware of the consequences of the application of the Red Queen effect to technology. The landscape around you is changing and accelerating as you create and learn yourself, leaving you with that bittersweet taste of always having more work to do than what you’ve already done.

So the Job Board is not a beautiful piece of art you and your team create in an afternoon and can then be encased in glass to be admired. It’s a living organism you print, tack onto a wall or a whiteboard, make changes to as you learn more about the job, get more insights and redefine your success criteria.

A working example

You’re an on-demand food delivery startup with some traction. You’ve talked to your customers and they’ve told you that things work well for them when they’re alone, but when they have friends over, they need to order larger quantities of food easily — an competitor for the job would be to just go out for burgers or call Domino’s.

JTBD

When I have friends over and don’t feel like deciding what and how to cook something, I want to get something easy and filling, so we can get on with playing Cards Against Humanity the rest of the evening.

Insights

“80% of our orders are single-servings”, “Our funnel drop-off rate when people are ordering multiple servings of the same product is 50% higher”, “In user research, people report making multiple orders when they have friends over”

Hypotheses

  1. Based on the insight that 20% of our offers are for multiple servings, we believe that by introducing a Group Deals category we will allow people to easily find food for their group of friends, simplifying their selection process after a search.
  2. Based on the insight that people report making multiple orders when they have friends over, we believe that letting people order from multiple restaurants at once will allow us to better serve groups, increasing conversion rate for these orders.

Success

We will see a positive impact in conversion rates for people ordering multiple-servings.

In the 1st month following launch we will see the total number of orders by our “group-orders” cohort increase by 10%.

User Experience

Experiments

  1. We predict that by creating special Group Deals based on aggregating offers, we will help people find large portions to feed a group for the night. We will test this by introducing a Group Deals CTA and assuming the change has no effect (the null hypothesis) and running an experiment for 2 weeks. 
    If we can measure a 5% statistically significant change in search to conversion rate, then we reject the null hypothesis and conclude there is an effect.

Finish your order

An example early stage Job Canvas

The Job Canvas is never finished. While your team stays focused on solving problems gravitating around a key job-to-be-done and while customers are ditching your product for competitors, there is work to do. The Job Canvas gets updated, new insights are collected, your success criteria evolves and new experiments are launched. Your User Experience prototypes go from low-res to high-res and your team grows with the canvas as it evolves.

Take it for a spin, and give me a shout when you’ve tried it with questions and suggestions — The Job Canvas is never finished!

The Job Canvas is one of the plays I describe in my Product Playbook, a set of Product Tactics I’ve been putting together. Check it out on github, and download the template for free, give the other plays a look, contribute to the playbook and give me your feedback.

Also, say hi on twitter at https://twitter.com/colivetree.

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