Analytics consultants sometimes forget that "Slicing and Dicing" is a form of data preparation. Here are some ideas to make your organization better at being data-driven by making that prep part of the process.
Slice and Dice: Two Words That Undermine Your Analytics Efforts
Have your analytics consultants ever said this? “And then your users can slice and dice the data from there!” I’m guilty of using it in my career. We probably all are. It implies the hard work is done. The checkbox can be officially checked. We can move on to the next effort. It implies it is now up to the users to do something with all that great work we just completed.
But wait… If there is still slicing and dicing to be done, we didn’t complete our analytics effort. We didn’t answer a business question. We didn’t influence or automate business decisions. We just gave someone else data so they can do the analysis. If your effort ended with you giving the users data and not answers, your effort was data engineering. It could have been part of an analytics project, but it was not analytics.
How do you push your organization beyond the delivery of data and into driving business value? It starts with understanding what happens in that “slicing and dicing”.
For the Love of Analysis
What are your users of data doing in Excel, PowerBI, and Tableau?
That’s one of my favorite questions to ask. Especially to I.T.! Whether you know it or not, these users are driving the vast majority of the business decisions in your company. Their spreadsheets, charts, graphs, trend lines, R-code, and Excel macros are informing and influencing leadership decisions. Don’t believe me? How many large Excel files does your finance office have and can your finance office function without them?
Using I.T. language, these users are doing additional transforms on the data and producing additional visualizations. Using analytics language, they are doing data preparation and additional analysis (anywhere from descriptive to prescriptive).
If you want to make an impact on how analytics is performed in your organization, you must embrace these users of data and their capabilities.
Serve the Dish, Not the Ingredients
Data-driven decision makers want their data-driven solutions served without additional preparation needed. I liken it to the analogy of a “Hello Fresh” pizza vs “Delivery” pizza. Probably the same outcome at the same price, but the Delivery pizza doesn’t require a decision-maker to be a chef or take the time to learn to be a chef.
If your analytics project is serving ingredients and not a dish to your users, here are two actions that will help:
- Ask more questions to the consumers of the analytics to better understand the purpose of the effort. This allows the analytics team the opportunity to embed all the preparation needed into the solution.
- Empower analysts to execute their portion of the analytics project in a tool that has some repeatability and automation capabilities like Dataiku. Repeatability and automation features will save you time and reduce errors by eliminating future manual analysis or Excel mishaps (aka Spreadsheet Risk).
Empower your analytics team to drive closer to the business decision. Be wary when you hear slice and dice! If your users are asking to slice and dice their own data, take that as an opportunity to learn more about your business and engage to help them automate that further data analysis.
Need some help being more data-driven? Do your decision makers need a data-driven decision? We can help. Let's chat.