You don’t need Artificial Intelligence, you need Active Information

You may think that AI is the solution but are you even making the best use of the information you already have?

Last week I was having a chat with my friend and entrepreneur Mike in a coffee shop the other day and the subject turned to AI.

During the discussion, we came to the conclusion that most businesses considering using AI don’t understand the data they already have or could have. Often these jewels of information are in disparate locations, difficult to use formats or not even captured.

As we both enjoy a good simile we analogised this data to reservoirs whose locations are not even known let alone used to power electric turbines.

Often these businesses jump to a solution (data warehouse, data lake, data lakehouse..) without even understanding what the data is, how it might be used and how much it will cost to get it fit for use, let alone the opportunity costs of not utilising it.

It sounds counter-intuitive but I tend to build data strategies, tactically, one question at a time, incrementing to build towards a coherent approach, learning as I progress.

I’ve worked with dozens of clients to:

  1. Identify the key value propositions.
  2. Identify a manageable number of metrics for this value.
  3. Build systems to capture and broadcast these metrics.
  4. Ingest and transform existing data sources.
  5. Blend existing data and metrics to answer a specific and manageable number of questions.
  6. Identify actions and implement them.
  7. Repeat from 1.

Often this process can identify data you already have that’s not readily usable because:

  1. You weren’t aware you already captured it.
  2. It’s in a format and/or location that makes it unmanageable.
  3. It’s missing a key dimension you’re not already capturing.

In a lot of cases, the missing technology that’s preventing you from getting value from your data is data engineering and not AI.


If you want to discuss how to release the potential of your data please contact me through the comments, email or LinkedIn.

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