Digital Transformation: Preparing Your Organization For A World Of Constant Change

Bill Schmarzo

“It is hard to teach an old dog new tricks. They’ve only been in business for 155 years.” – Anonymous

The Pullman Co (1867), Allied Corp (1920), Heinz (1869), Hughes Tool (1908), Ford Aerospace (1956), Motorola (1928), Bethlehem Steel (1857), Ralston Purina (1894), Compaq (1982), E.F. Hutton (1904), PaineWebber (1880), MCI (1983), Eastern Airlines (1926) and Pan Am Airlines (1927), Houston Natural Gas / Enron (1940), Arthur Andersen (1913), Woolworth’s (1879), Standard Oil (1870), General Foods (1895), Kraft (1923)…

A recent article by Peter Bendor-Samuel highlighted three reasons why an organization’s digital transformation fails:

1.     Lack of up-front (senior management) commitment

2.     Failing to take an iterative sprint approach

3.     Taking a technology-first approach

Totally agree. Each one of these three is a non-starter if you are serious about successful digital transformation. However, while each of these reasons is relevant and needs to be addressed, I find that the underlying premise of the article is wrong – that “fatigue from continuous change is a top reason why more than 70% of digital transformations fail.”

Continuous change is not why digital transformation fails; the lack of continuous change is why digital transformation fails.

Four survival tips to help organizations thrive in the future

To be successful at digital transformation, your organization must embrace the power of continuous change and learning: the digital transformation survival tips.

Survival tip #1: Digital transformation is about species survival

Organizations must instill a culture that continuously challenges the existing norms – a culture that embraces change as the only constant for business model (species) survival. Charles Darwin proposed that species evolution is a natural selection process. Because resources are limited in nature, organisms and organizations with heritable traits that favor survival and reproduction will tend to leave more offspring than their peers, causing the traits to increase in frequency over generations.

How do you prepare your organization for a constant world of change? Embrace design thinking. Understand, teach, and live the human-centric, humble-management design thinking concepts and approaches. Make them a daily part of the operations of your business, and not just another management fad.

Everyone can learn from everyone else if you embrace a culture where all ideas are worthy of consideration and if you don’t have enough “might” moments, you’ll never have any breakthrough moments. And by the way, don’t believe that only the best ideas must come from senior management. That’s the command-and-control management way of thinking.

Survival tip #2: Have and live a “true north”

A “true north” can’t just be a statement that the senior management team constructed in their latest off-site. A “true north” should be why the organization exists and the value it provides to society.

Our “true north” is a commitment to help our customers (both external and internal) become more effective at leveraging data and analytics to power their business models.

It’s about embracing a value engineering approach that helps organizations identify, validate, value, and prioritize their key business and operational use cases – a process to help derive and drive new sources of customer, product, and operational value.

Survival #3: Identify, codify, and operationalize new sources of value

Digital transformation requires organizations to master three aspects of value creation: identifying, codifying, and operationalizing new sources of business value.

In detail from the figure above:

  • Step 1: Embrace an envisioning approach to bring together all key stakeholders to identify, validate, value, and prioritize the organization’s key business and operational use cases. This is the world of design thinking. And make sure that all key stakeholders are engaged; otherwise, you run the risk of being torpedoed by passive-aggressive behavior.
  • Step 2: Codify (capture in software and math) the sources of customer, product, and operational value. This is the world of data engineering, DataOps, and data science. Yep, this is where those giant-brained data scientists will leverage AI, deep learning, machine learning, and reinforcement learning to “identify variables and metrics that might be better predictors of performance” and “extract commonalities from data distributions to aid in the identification and classification of objects.”
  • Step 3: Operationalize (embed) the codified sources of customer, product, and operational value into your operational systems. Think about where and how to leverage the codified customer, product, and operational insights to optimize, automate, and eventually create an autonomous value chain, or value network, while reengineering your business model.

Survival tip #4: Embrace a culture of learning, sharing, reuse, and refinement

This fourth survival tip may be the hardest because it’s based on creating an open and transparent culture that seeks to give everyone in the organization a voice…and an opportunity to co-create value with other members of the organization.

The unique economic value of data and analytics – two digital assets that never deplete, never wear out, and can be used across an unlimited number of use cases at near-zero marginal cost – is founded on the principle of learning, sharing, reusing, and refinement. Every time you use the data and the analytics, those assets have an opportunity to get better – more accurate, timelier, and more predictive:

The Schmarzo Economic Digital Asset Valuation Theorem outlines three economic “effects” that are the result of sharing, reusing, and refining the organization’s data and analytics digital assets:

  • Economic Effect #1: Marginal costs flatten. Since data never depletes, never wears out, and can be reused at near-zero marginal cost, the marginal costs of sharing and reusing “curated” data flattens.
  • Economic Effect #2: Economic value grows. Sharing and reusing the packaged/operationalized analytic modules across multiple use cases drives an accumulated increase in economic value.
  • Economic Effect #3: Economic value accelerates. The economic value of analytic models accelerates because refinement of one analytic module lifts the value of all associated use cases.


Let’s take a lesson from Charles Darwin about species survival and prepare ourselves to not only survive but actually flourish in an age of continuous change. And start that organizational preparation by embracing the digital transformation survival tips.

Species survival is a lot easier when you empower the entire organization for the inevitable change being driven by digital transformation.

This article originally appeared on LinkedIn and is republished by permission. Hitachi Vantara is an SAP global technology partner.


Bill Schmarzo

About Bill Schmarzo

Bill Schmarzo is CTO, IoT and Analytics at Hitachi Vantara. Bill drives Hitachi Vantara’s “co-creation” efforts with select customers to leverage IoT and analytics to power digital business transformations. Bill is an avid blogger and frequent speaker on the application of big data and advanced analytics to drive an organization’s key business initiatives. Bill authored a series of articles on analytic applications, and is on the faculty of TDWI teaching a course on "Thinking Like A Data Scientist." Bill is the author of “Big Data: Understanding How Data Powers Big Business” and "Big Data MBA: Driving Business Strategies with Data Science." Bill is also an Executive Fellow at the University of San Francisco School of Management, and Honorary Professor at NUI Galway at NUI Galway J.E. Cairnes School of Business & Economics.