Why Digital Transformation Should Start with Knowledge Not Data

Author: Donald Thompson
Why Digital Transformation Should Start with Knowledge Not Data

In our latest blog Human Knowledge: The Crux of Digital Transformation, Maana CMO, Azita Martin, explains why capturing human expertise is just as important as using the right data for digital transformation.


Maana’s customers are some of the largest industrial companies in the world, operating highly sophisticated equipment and processes.  We built our software platform working closely with these companies to optimize their assets and decision flows.  Everything Maana does starts with the business problem and the objective of what the customer wants to achieve. That is why we have built a platform that can be used for collaboration between the subject-matter experts who understand specific operations or decision flow, and the business analysts and data scientists.

For example, in a scenario where a company is looking to optimize the maintenance of its turbines, the asset maintenance expert—responsible for turbine maintenance—has valuable expertise that is key to achieving desired outcomes. He or she understands the physics of how a turbine operates, the physical properties of the turbine, and the current processes and resources used to maintain them. This knowledge is incredibly valuable in helping companies ask the right business questions that collectively solve a major business problem.


That is why we believe, before jumping into the available data, the first step is to ask the precise, pressing business question in common business language. To return to the turbine maintenance example, the company might ask, “Given a particular engine’s operational and maintenance history, and the planned job schedule for this engine (asset), what are the most likely failures?” This is an important question because it investigates a relationship between common business concepts such as engines and maintenance histories. The answers to these questions drive decisions that optimize and prescribe the appropriate maintenance weeks in advance of equipment failure, while reducing unnecessary maintenance costs.

Before digging further into the world of knowledge, I want to clarify some basic terminology by answering the following questions:

What is a model

A model is the digital encoding of data and human expertise that provides actionable recommendations into specific decision flows. Knowledge is captured in the form of models. Any solution that claims to be able to digitize all high-impact assets and workflows (100+ for a large enterprise) should be able to do so at scale and speed. The best way to achieve that is through modularity. By representing each workflow as one or more models, one can create a currency of digital transformation that can be minted, applied, re-purposed, and tracked.


What is digital knowledge?

Fundamentally, knowledge is the answer to a question.  We’re talking about a specific, crisply-defined business question (let’s call this a problem-question) and a series of subsequent follow-up questions that best describe the problem at hand. Digital knowledge, on the other hand, is a network of models that collectively provide recommendations for a specific decision flow so that employees can make better and faster decisions.


An enterprise can have virtually limitless knowledge sources—and it’s easy to be overwhelmed by them. With the Maana Knowledge Platform, any kind of problem solving must start with a question. Without this, it’s nearly impossible to know where to start in order to arrive at the answers you need.


Why take a knowledge-first approach over a data-first approach?

The problems you are trying to solve should determine the problem-questions you ask and the data you need to answer them. That’s why starting with data exploration and analysis—before you understand exactly what you want to know—can waste time and resources.


In contrast, by taking a knowledge-first approach supported by Maana’s knowledge platform, all collaborators (for example, business leaders, analysts, knowledge workers, data scientists, IT experts, etc.) can agree upon the problem-questions, represent them digitally in the form of models, and simultaneously capture the relevant data, knowledge expertise, experience and decision-making skills to generate digital knowledge.

In my next blog, I will talk about the benefits of a knowledge-centric approach vs a data-centric approach.   But to get a feel for how companies like GE, Maersk, Chevron, and Shell are using the Maana Knowledge Platform for digital transformation, take a look at some of the optimization initiatives these companies have accomplished. Each of these use cases has delivered business value in less than three months, and quickly led to digital transformation initiatives across the entire enterprise.



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