When people execute a job (the job executor), they have specific outcomes and results they want and expect. For example, when doing the job of mowing the lawn, the desired outcome is to have a well-manicured lawn that looks great.
The job executor also wants the actual execution of the job done as well as possible, not just the ultimate outcome (i.e. a manicured lawn), but all the steps it takes to complete the job. For example, when we mow our lawn, we want the product we hire, let’s say a gas lawn mower, to start on the first pull, catch the cut grass for us automatically, and cut the lawn uniformly without scalping it.
How well are customers getting their important jobs done?
If developers want to improve an existing product or to create a new product, they must figure out where the customer struggles in the execution of a specific job and then devise ways to help the customer get the job done better.
A job can be as simple as mowing the lawn, or as complex as managing the flow of inventory and material through a manufacturing plant. Though at polar ends of complexity and financial investment, each of these jobs consist of discrete steps and decision making points.
In the case of manicuring the lawn. A job executor hires a lawn mower with the expectation that it can get his job done perfectly under varying conditions (for example different grass heights, steep slopes, wet conditions, etc.). Setting up the mower, fueling it, starting the mower, pushing and guiding the mower, emptying and cleaning the mower, and stowing the mower when the lawn is cut, are some of the steps involved in manicuring the lawn.
These steps define the “job-map” for one aspect (keeping the grass trimmed – the functional job) of manicuring the lawn. Note: a manicured lawn is the ultimate desired outcome and represents the top of the “job-tree.” Other jobs in this job-tree include, keeping the lawn green, trimming the edges, weeding, and so forth.
Job-maps provide a detailed visual map of all the steps involved in getting to a final desired result. Helping a job executor get these steps done better, or even eliminating unnecessary steps, is where our innovation activities needs to be focused. Job-maps and job-trees will be discussed in greater detail in future articles.
The operational manager has a more complicated job to be done. Managing the flow of material, parts and overall inventory to achieve maximum efficiency and throughput on her manufacturing floor and warehouse.
She will need to decide how much inventory, both in finished goods and work-in-progress, she needs to carry to make sure she can meet the production schedule sales has committed the company to.
She will need accurate sales forecast and manage her supply chain to make sure it can keep up with her demands, but not result in too much inventory at the end of the year. That would result in an “undesired” outcome she wants to eliminate.
And she will need to work with engineering services to make sure the documentation she uses on the factory floor is up to the current release levels. She doesn’t want to complete a sub assembly only to discover it is no longer up to spec. Another undesired outcome she wants to eliminate.
Indeed, the operational manager will have lots of sub-jobs and steps involved in managing her manufacturing floor. All these sub jobs and job steps define the job-tree and job-maps of the primary job a job executor wants to get done. In this case, running a lean and efficient manufacturing operation.
The point I want to make is that jobs are processes and methods that consist of multiple steps and decision points.Each step and decision point along a job map produce outcomes that the job executor desires, and undesired outcomes the job executor wants to avoid.
Success is defined at each step in a job-map
Whether we are talking about multiple jobs inside a job tree, or a standalone job, each process step of a job has its own set of desired outcomes job executors use to define success. Not just the ultimate outcome, but all the steps along the way from beginning to end.
Knowing desired and undesired outcomes at each step are equally important. These define the customer’s needs based on the functional job to be done, as well as provide a definition of “getting the job done successfully” from the customers perspective.
The real power of Jobs-To-Be-Done (J2BD) innovation approach comes from identifying and prioritizing a set of desired outcomes a customer wants to achieve in executing his job. Depending on the complexity of a “job,” we can expect to uncover 50 to more than 150 desired outcomes per job. We will explore how to prioritize underserved and important outcomes using the opportunity algorithm in a future article.
Capturing customers’ needs and requirements
Now of course, don’t expect a customer to be able to precisely articulate all of his desired outcomes to you. It’s not quite that easy because most customers aren’t thinking about their jobs in a structured innovation framework. It is up to us as researchers and developers to listen to and observe the jobs customers are trying to get done, and then translating the raw inputs into actionable information.
We will explore in greater detail how one gathers customers inputs, and how we translate these inputs into requirements we can innovate around, in future articles.
In the meantime, let’s go out and figure out what important jobs our customers really want done, and how we can make their jobs easier to do, with less time, less money and no hassles!
Here’s to doing a better job for our customers!