In this week’s Process Session, we talk about the importance of selling your process model benefits using best practice marketing tactics and approaches. The transcript below has been lightly edited. -- Sandeep: Selling the benefits of process modeling is difficult. In fact it’s one of the hardest things that any process modeling project undergoes. A lot of traditional ways of selling process models have been questioned before and some of them have not worked. Others may have but what we’re offering today is a fresh new way to look at how process models have been sold. More importantly the benefits of these process models. I’d like to introduce you to Daniel Weatherhead who’s our marketing manager in Leonardo Consulting. He is here today to answer some of our questions and provide some guidelines on how process modeling or models can benefit from a marketing perspective. Welcome to the show Daniel. Daniel: Thanks Sandeep. It’s great to be here today. Sandeep: So before we get into actually answering the question of how process modeling can leverage marketing, let’s get some of the basics correct first. So Dan in your point of view, what are some of the basic techniques the world of marketing can inform and can educate the people in the modeling world? Daniel: What we’re talking about is a shift - a shift away from what we would call the old outbound marketing tactics. These are the tactics of the previous generation - the generation before. Interruptive tactics that don’t necessarily look to inform and educate but were very much placed there interruptively into people’s lives. Now think about your television ads, your radio ads, your newspaper, advertisements. These are the sort of things that shout at you. They are one-way traffic. People didn’t necessarily go seeking those messages.
How do you know when you've come across a good process model? Do you use your gut feel or do you actually quantitatively assess how good a process model is. Interestingly enough, there's very little out there that describes how to assess whether a model is good or not.
Have you been asked to do a process model and you just don't know the amount of detail that you need to do a successful process model? The level of granularity that you have in your process model will determine how useful it will be.
In life there are things that you cannot control, like the weather or the release of the next iPhone. Fortunately enough, there are things that you can, like process models. Imagine a world where everyone creates process models and there are lots and lots of people who submit in all this data into a central location. What you're gonna end up with very quickly is a mess. You don't have to imagine this. It happens right now. I share with you three very simple steps you can undertake to ensure that you've got a robust governance structure to handle this mess. In the world of process modeling, it's often the case that a lot of people create lots of good content. Everyone has the right intention. They want valuable models, they want useful stuff, and most importantly, they want to contribute. However, very quickly, when there's a lot of people involved in creating process models, you end up with a big mess. One way to handle that big mess is to understand some structures and place some measures that you, as a leader, in this space can ensure that the content that is produced is still valuable, useful, and well-understood by everyone who use it. So here are the three steps that you can undertake to ensure good governance across process model creation.
Every single process model that you create is part of a larger ecosystem, an ecosystem of dependency and relationships. It definitely is because in real life, your processes are related to one another. In this video, we talk about what that ecosystem framework is, and how to place your models in there. Every single model tells a story of the organization, a story of how processes deliver value. However, on its own, it may not fully describe what's going on. More specifically, it may not describe the relationships and the dependencies, which means that each process model that you create on its own may not be able to show you an impact cause at the start of the process, and its effects downstream.