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Building a Data Knowledge Diamond

Upskilling, data literacy, data fluency and even data culture are interrelated and often simply smashed together. I’m not brave enough to wade into this semantic war, instead in this next series of blogs I will build off the framework below in an attempt to answer a simple less buzz wordy statement; “what should each level of my organization know about data and analytics?”

Every organization is different (not to mention every human), so I will lean on principles and generalities in an attempt to help you build out or inform your own efforts. In this way your Data Knowledge Diamond will be unique, as all organizations and diamonds are.

Key Principles for Adding Data Knowledge to Non-Data Functions

Our clients (F1000 sized and analytically ambitious) indicate that 80% of data education efforts are aimed at “non data”* functions and those functions are represented by the diamond above. Education efforts for these functions should follow these principles:

  • Everyone from the CEO to the hourly co-worker needs to have time set aside for data education and training designed to connect to their work
  • The volume of time increases as you get closer to the middle of the organization
  • The depth of training increases as you get to the middle of the organization
  • The hands-on nature of actively working on analytics increases as you get to the middle of the organization
  • From the bottom or the top, subjects are added as you get to the middle
  • The bigger the company, the more strata in the diamond. This diamond represents your average F1000 company and is biased towards my retail experience

* To borrow from Shilpam Pandey, “everyone’s a data person they just don’t know it yet.”

The Facets of the Diamond

Below are broadly what each function should know in the area of data and analytics. It’s reasonable to see the more or less could be added to each box, so long as the principle applies – those in the middle need to know more and know more deeply.

Throw Rocks or Share Your Perspective

Surely you noticed that this framework is a work in progress, or in data terms a POC. I decided to share it, as undeveloped as it is because I have been in dozens of conversations with brilliant thinkers from experienced execs, to focused upskilling consultancies, to universities; and while everyone had great ideas about how to train on a given subject, no one had a way to plan out the larger program or a simple way to express the natural variation. So, I will build on this framework in coming blogs and highlight from my professional experience, client interactions and research: the concepts, approaches and programs that are used to successfully increase the knowledge in the right amount to the right level. I welcome your suggestions, thoughts and ideas, so we can build this out together.