When you don’t know what you don’t know: A tale of Corporate Strategy.

When you don’t know what you don’t know: A tale of Corporate Strategy.

Should we increase commission on a new product that we have in our offering to see if this will correspond to an increase in revenue and what will be the underlying cost of our projections?

Pretty simple question, yet I bet if I asked for the proof behind the answer, it would take a fair amount of you months to provide something that would be less than embarrassing. In a day and age where everyone hears the term big data, so few of us really know how to connect it and derive anything meaningful. I know there is a group laughing out there, hahaha “this clown and those people are clowns for not knowing”.

Sure, laugh away, but you’re just as bad. The reality is I have been at countless small and large customers, from SaaS companies to manufacturing. I have seen with my own eyes, even the most technologically advanced companies get mired in figuring out how to piece all of it together.

Even former Secretary of Defense, Donald Rumsfeld, reflected on the conundrum of what we know and what we don’t know (albeit on a slightly different subject):

“Now what is the message there? The message is that there are no “knowns.” There are things we know that we know. There are known unknowns. That is to say there are things that we now know we don’t know. But there are also unknown unknowns. There are things we do not know we don’t know. So when we do the best we can and we pull all this information together, and we then say well that’s basically what we see as the situation, that is really only the known knowns and the known unknowns. And each year, we discover a few more of those unknown unknowns.”

So where do we start? Well, what is it that the strategy your people use to model, what is the process by which they go out to get the data to prove anything? If there isn’t one, you may be better off, hear me out on this. What you need to handle the first part of this is an ability to tie all the sales operational data into a central place. Many think this is a commission engine to do modeling and what if.

I would challenge that as commissions will only have commission eligible events. I think for the question at hand you must look further back. You must look at bringing in your entire sales structure and marry it to your commissions for a holistic view of the effect from sales, to revenue to cost. Now that we know this, lets go find where it exists and how to manage this endeavor.

We know there is a POS or CRM system that is capturing sales activity and deal movement. We also know there are HR systems and commission systems, along with our accounting that may have other relevant information. If we want to look at the structure, we should understand what portions of these we should look at replicating into our reporting engine.

Yep, our BI tool that will allow us to take the information, link it, and report it out in a meaningful way. After all, anything cool comes in a report, but the devil is in the details. When looking at this undertaking there are a few key considerations:
1. Not to be captain obvious, but the BI tool and its capabilities.
2. The platform by which you will house the data.
3. The method by which the data will be entered and cleansed.

Sounds simple enough but here is where considerations must be made. On the BI tool, what are your full intentions? Will this plug into another interface? (better validate that it loads into your interface structure and has been thoroughly vetted). Can you build widgets in a frame without implicitly having to use their application front end? How does it allow users, end users, to generate their own reports?

On housing the data, a big term now is the data lake. Whether it is a lake that you pull from and a cube or warehouse you push to, the concept of the structure of where the data lands is of the most importance.

Entering and cleansing data is an animal of its own. This is of importance, because to infer any type of meaningful information, one must ask the right questions, and take said answers in a way that can be categorized quickly without prejudice. People spend their lives on doing this type of work, it would be a disservice for me to boil it down to a paragraph. I might suggest reading “Belief in the Law of Small
Numbers”.

While this is clearly an oversimplified start and explanation, it is a brief introduction to a few areas that need to be considered. Look for our White Paper on this very topic along with future blogs on statistical analysis in sales decision making process.

  • On March 28, 2018

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