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Understanding Digital Transformation


George Danner, President of Business Laboratory, recently talked through how to transform a company by rethinking, reimagining how it could work with a digitally connected enterprise (customers, partners, things, and systems) with intelligence from the data driving decision-making processes. Learning more about digital transformation is key in the everchanging world we live in, and Danner’s presentation helps users understand it and learn from professional sports about how analytics has transformed the way sports teams organize themselves, select players, establish strategies, and win.

Even before the COVID-19 pandemic, there was a trend toward high levels of automation in today’s economy. Now, we can expect an even greater demand for automation. It will be a permanent fixture of our economy. The companies that succeed will be those that embrace high degrees of automation. Those that do not survive will likely be the ones that cling to outdated business models, now surpassed by the automation trend.

Digital Transformation Basics

Digital transformation as an offensive weapon can make your company better, faster, and cheaper. As a defensive weapon, it wards off competitors and keeps the company running through unprecedented scenarios. Automation is part of the answer to global disruption, and digital transformation as a concept is in the eye of the beholder. Danner’s definition for the intention of this presentation was “Automation using digital technology with an economic purpose.” That statement can be broken down into three main focus points:

  • Automation: Deploying certain technologies for the purpose of making things work without huge amounts of human intervention.
  • Digital technology: Appropriate mapping occurs from the list of the art of the possible. The art of the possible is a list of every interesting thing that can be done fundamentally with technology. The key is choosing the right complement of technologies to bring to bear the problem at hand.
  • Economic purpose: The driving factor behind any digital transformation— increasing your economic value. A lot of companies view digital transformation as an IT project. While IT efforts are necessary as a component, digital transformation is a company-wide economic value.

Digital transformation is all about working backward from the business problem, then mapping the appropriate art of the possible collection of technologies to that business problem.

Digital Twin

A cornerstone concept in digital transformation is the term “digital twin.” A digital twin is a digital replica of a real system or asset. All information and history that exists about the real asset, exists in the digital twin. This replica creates a safe test environment for your company.

While making one adjustment that will exponentially increase your organization’s economic value seems ideal, the reality is that it usually takes a series of interventions working symbiotically for overall economic value generation. This is why a digital twin is incredibly advantageous.

The digital twin allows you to stress test your strategies. You can create an environment where experimentation is encouraged and facilitated. Take theories about the business and apply them in the digital twin. Aim for a strategy that holds up against a wide variety of situations, even those unprecedented.

The process for automating large scale systems and creating digital transformations is laid out in detail in Danner’s book The Executive’s How-To Guide to Automation. This is the outline:

  1. Create a hypothesis. This is your goal for automation. Taking time to clearly and succinctly elaborate the hypothesis will pay off in downstream benefits.
  2. Through a process of modeling (detailed in Danner’s books, Profit from Science & The Executive’s How-To Guide to Automation), create a digital twin.
    1. As you are building out the digital twin, a group of function maps will emerge. These functions can be carried out by humans, machines, or computation. All of these are documented.
  3. From interacting with function maps and subject matter experts, create an inventory of algorithms in use related to the physical asset. This documentation is the intellectual property of the firm. How you do something and why you do it should be put on a piece of paper to create value and continuity for the company.
  4. Simulate automation in stages.
  5. Implement automation.
  6. Repeat steps 4 and 5 until full automation is reached (the ultimate economic prize).
    1. Observe the labor content of this physical asset per unit of output. It should start declining if the automation is effective.
  7. Redesign the physical system.
    1. An example of redefining the physical system that currently exists is a completely unmanned restaurant that a popular restaurant chain has created and installed for workers.

Examples of Digital Transformation

Artificial Beam Lift Well Case Study

The problem: Artificial beam lift oil wells are managed by field engineers. It takes a field engineer three to five years to learn how to take care of them. One field engineer takes care of 30-40 wells in the oil field. They learn this process by shadowing a current field engineer. The oil well company wanted to shorten the training time frame for becoming an effective field engineer with the use of data already in-hand.

With Danner’s help, the company created a digital twin of an artificial beam life well with subsurface material. They put this into a simulator. All of the data and actions at a field engineer’s disposal in the real world are available in the simulator. A scorecard keeps track of money being made and spent. It allows field engineers to learn how the actions they take in the field take effect economically.

To create the digital twin, subject matter experts in the company (field engineers) described the things experienced in managing a production machine. This was committed to paper. Other conversations were also committed to paper. Ultimately, a blueprint was built which allowed the company to ease into building the digital twin.

Healthcare Organization Case Study

The problem: A healthcare organization wanted to run tests to determine their strategic policies. They needed answers to questions such as:

  • How many hours should we be open?
  • Should we accept emergency patients? If so, how?
  • What is the model of care?
  • How do we route patients to another healthcare facility?

All of these strategic questions arose regarding managing this complex United Kingdom health system. They had the ability to set parameters and create infinite worlds through their digital twin. Then, they could calculate the implication of each world.

The data for the digital twin already existed. It simply needed an analytical forum to test various theories about policy cause and effect. Cost and performance metrics allowed them to evaluate the world that was created in the digital twin for overall economic value.

Quick Tips & Tricks

Here are a couple of quick tips and tricks from Danner’s presentation:

  • Diagrams are the language of systems. You will help yourself if you acquire the skill of making clear, simple diagrams that show objects and their relationships.
  • Automation can and should be done in careful stages.

A good modeling process is displayed below:

When creating a diagram of a particular asset, you are replicating all of its functions. Interestingly, you have the opportunity to build the diagram in such a way that the pattern reveals itself by the very act of creating the diagram in the first place.

Structural patterns of assets are elaborated in Danner’s book. According to Danner, if you lay out a company from end to end, the entire processing is not best suited for automation. The key is to create surgical doses of automation at just the right places.

Below are two examples of diagrams:


Next Steps in Digital Transformation

The digital transformation movement is headed toward the idea of a knowledge system. Knowledge systems occur when all digital twins reside in one place. This creates the opportunity to ask natural language questions about the state of systems and receive sensible answers.

Wolfram Alpha is a knowledge system. If the following questions were asked to a standard search engine, the results would be inaccurate, unfound, or nonsensical. The knowledge system is able to respond to complex questions, as displayed in the examples below:

Key Takeaways

In the current state of economic distress, aim to create strong, fast, resilient companies through digital transformation. Rewire your business by questioning everything and applying strategic theories with a digital twin. Remember, digital transformation is not strictly a technology and data design. The bottom line of digital transformation is economic value.

For more information, check out Danner’s full presentation attached below.

Understanding Digital Transformation