Data, business, sales, insights, and revenue are popular keywords found in abundance around the internet these days. As a Founder of my own company, I can certainly understand the need to focus on such keywords in daily, weekly, monthly, and quarterly discussions.
But, as a Data Analyst, not all keywords are created equal for each role in the company. Let’s simplify and break the business hierarchies down to three levels, which have a direct impact on how data can be used:
- Executives: The top of the chain that defines long-term strategy, implementation, and overall decision making.
- Manager: The mid-level staff responsible for action of strategy, interfacing between the needs to the subordinates and the Executive teams.
- Operational: The largest population of the business with the responsibility to make it happen by pushing the buttons, interfacing with customers, and carrying out decisions hour by hour.
This three tier pyramid of decision making in a business is streamlined to illustrate key areas that any serious Data Analyst should have on their radar. These are important for classifying stakeholders, understanding information flow, and who is accountable for goals.
If we take this a step further and define each classification with a time period pertinent to their interests, you will see a classic roll up of data. In this example, we will assume we are working with a simple SaaS company with a single product.
- Executive – Monthly & Quarterly & Annually (simple, direct, top level information)
- Manager – Weekly & Monthly & Quarterly (Annual is usually irrelavent to mangers, except budget owners)
- Operational – Daily & Weekly & Monthly (Quarterly and Annual metrics are usually irrelevant to operational staff)
Now, if you are most other business stakeholders that I have this discussion with, you are probably about to ask, “Why aren’t quarterly and annual metrics important to operational staff?”. To which I answer, “operational staff with effective goals merged with metrics would have taken action long before the quarter or annual numbers are even reported, because it is their responsibility to meet their goal, typically set to be achieved weekly or monthly”.
Data hierarchies are some of the most fascinating aspects of a business because each level has goals timed appropriately to roll up to the top. If a quarterly goal is missed at the Executive level, one should know automatically where the inefficiency occurred and be making plans to fix it before the quarterly numbers get to the Executive team.
In short, the three levels of an organization are a fascinating jumping off point for developing a data strategy in a business, department or team. To implement an analytics plan without regard to the role and business structure is like bungee jumping without a rope. Don’t jump before making sure you understand what insights, sales, revenue, and data mean to the hierarchy you are working with.