Why is the business purpose model (s) so difficult? – Sylvester Blog

Why is it so difficult to develop a high-quality business purpose model?

The Business Objective Model (BOM) is one of the most powerful visual models we use in our projects. A good BOM not only defines opportunity, it also provides a mechanism for prioritizing product features and measuring project success. Not bad for a one page image! Our guideline is that each project / product team should create a business purpose model, ideally at the start of the project.

Yet, my own experience is that business purpose models are often incomplete or not done at all. It should be one of the easiest models to create and yet it is the most difficult. Why is that?

BOM is deceptively simple – a string of related problems and objectives that logically leads us to the concept of the product and its component features. But a good development requires both intellectual rigor and honesty. The process of creating one as a team reveals our inefficiency. It can be painful.

Sometimes when we teach people how to create a model, we use a simplified view so as not to get lost in the details. But for the purpose of exploring the challenges of BOM, I would like to use a more realistic example. You have an emotional response to it, that’s good! Because it likes to do this process in a project.

To test this thinking, we are going to pretend to be a member of a public interest group that is conducting research and making educational policy recommendations to the state legislature.

Let’s start with something that most people might agree on is a problem – that only 24% of American high school seniors demonstrate a “skilled” level of writing skills. It is easy to see that lack of skills will negatively affect college and work success for students. Let’s do this as our # 1 problem in the model.

Then we go to the first level of objectives. There is already the possibility of uncertainty and disagreement! Even if we agree that writing skills should be improved, we need to be as specific as possible and it is difficult to pin specific. Let’s imagine that we can agree that a 40% efficiency increase in 5 years is a well-expanded goal.

The next step in our modeling process is to document the second level of problems, the blockers that are currently hindering us from achieving that 40% efficiency goal. Now our stakeholders will carry a lot of statistics and studies and opinions. We need to evaluate them rigorously and honestly, as this will lead us directly to our proposed solution. If we become vague or inconsistent here, the whole model begins to crumble.

We have researched and discovered three important factors that contribute to students’ failure to acquire writing skills. These include lack of time spent on persuasive writing, lack of teacher education and resources, and lack of inherent grammar skills required to acquire better writing skills. This is a high-level model, so we will cover all of these, but of course there are many underlying complications of each of these problems. How much of these issues need to be analyzed at the moment depends on your organization and your existing skills. It may be that these are already well understood.

We then move on to the really difficult part – the final set of measurable objectives that are directly linked to the proposed solution. In my experience, this is where the model can really get thematic. Who decides which metrics should be used? Is the matrix actually measurable in real life? Is it possible to achieve this objective realistically? What are the hidden downsides to this purpose? I’ve seen a lot of real-world projects where we were unable to commit stakeholders to the metrics and had to resort to “x” as a placeholder that was never updated. This weakens the model, because without this metric we cannot use it successfully to evaluate and prioritize the proposed features. Consider our example. If we aim to develop a grammar tutorial without metrics so that it can be rolled out 100% in elementary school, then later, an argument can be made that 10% rollout has been successful. But in reality it will not have the desired effect on the real problem! There is analysis behind each of these ultimate objectives, because in order to narrow it down to this list, we need to do enough research to identify these best possible choices to guide our product design. There may be other approaches, but we exclude them because they are unproven or unrealistic or prohibitively expensive. Therefore, our model does not represent the entire universe of possibilities, but only those that survive in our analysis.

Finally, we list the proposed features of our solution. Each of these must be clearly linked to one or more of our purposes. The next logical step in this process is to create a cost / return on investment profile for each of these features to determine the best way to spend limited funds to achieve maximum value! For this, a purpose chain is the perfect tool.

Now I bet you are already thinking about the flaws in this example model and ways to improve it. Great! The best way to master the use of business purpose model is to apply it in different practice situations and work through reasoning yourself. The goal is to design the best possible solution to the problems we are working on.

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