Analyze Everything!
How To Ruin Your Business With Data & Analytics — v.3
Data is powerful. It can be a tremendous force capable of powering your business to the next level of growth and achievement. It can help you to make difficult decisions, determine true priorities, and provide astounding insight.
OR, and sadly with equal frequency, it can drain your budgets, waste your time, and lead you down the wrong paths. Data creates authority. Authority can be misused. It can be weaponized. It can be abused. Analytics can also be overused, leading to waste and delay. Neither one should be taken lightly. The greater the I, the larger the R required to justify it.
I have often noted that analysts are typically better at declaring what won’t work rather than what will. It is always easier to disprove a hypothesis. So, with that in mind, this series will focus on the common analytic decisions that lead to disaster. Each volume will detail 3–4 of those decisions and the reasons to avoid them.
VOLUME 3 — Prioritization
Analyze Everything
Analytics is a powerful tool for any business. So naturally, you will want to apply it everywhere! Of course, this is also a great way to waste time and money. Anything that is truly powerful takes time and money. Conversely, bad things happen when you put jet fuel in a moped.
Everything doesn’t need to be analyzed. In fact, the first thing to analyze is what truly needs to be analyzed. You need to identify the most important things, the most leverage-able things. In other words, leave the moped be — save your jet fuel for an actual jet. If all you manage to do with analytics is determine what needs to be analyzed, you have gotten farther than many. The next question is how much time and money did that require?
Analysis is learning and decision-making. Deciding what to spend your resources learning is the most important thing. Actually, learning what NOT to spend your resources learning is more important.
Don’t Waste Your Resources Collecting Data
If it is important not to waste your time and money on meaningless or unleverage-able analytics, clearly it is best not to waste money collecting endless data. Right?
Not in the least. Data collection is cheap. It is fast. THIS is NOT where you want to cut corners. Collect as much as possible. You can store it cheaply. You may never use it. But if you need it, it will be there.
I have witnessed more projects kept within budget (or more often timeframe) by ejecting data collection. This almost always results in projects that ultimately fail. A problem is inevitable — without data, you won’t be able to analyze it (even if it is clearly the most meaningful and beneficial thing you need to learn). Save your money somewhere else!
Let Your Business Units Prioritize The Learning They Need
No one knows what they need more than you right?
“Doc, I know you want to treat my failing kidneys but I am far more concerned with my yellow skin tone.” — said by nobody
Analysts are highly trained professionals (or at least they should be). Telling them how to do their job, what to prioritize, and generally micromanaging them is a fast path to wasting your time. If this function was worth funding, they are also worth trusting.
So many companies undermine the value of their analytics organizations, this section is likely to be rejected by many readers. Large enterprises often decentralize their analytics functions specifically to hold their prioritization accountable to individual business units. It is a common practice. Certainly, what is common — must be right. Right?
Analytics is about learning and decision-making. Who better to learn and decide what to learn and decide? If you are still struggling with this, think real hard about who your hired…
SO, if you are looking to ruin your organization with data & analytics — start by analyzing everything, collecting nothing, and letting your business units set the analytic prioritization. You will quickly burn through a lot of cash, launch a number of hopeless projects, and generally waste a lot of time.
Successful companies collect as much data as possible. They give careful consideration to the analytics they want to resource. They rely on their analysts to develop the prioritization. This doesn’t mean they waste money on high availability storage for lower priority data. It also doesn’t mean that the business units are locked out of setting priority.
This is only the start. There are plenty of other great ways to ruin your company with data & analytics. Stay tuned. And thanks for reading!
For help doing it right and early:
