There’s a growing body of evidence demonstrating technology-led digital transformations are overpromising and under-delivering returns on investment for owners in asset-intensive organizations.

According to McKinsey & Co., 70% of digital transformations are failing to meet stated business goals. For industrial sectors like manufacturing, utilities, energy and mining the reports are worse, the rate can soar to 80%. That doesn’t mean these major projects aren’t providing any value, just that the ROI can and should be questioned as a good business decision.

Certainly, asset owners are spending millions or tens of millions of dollars on technology investments to revamp their enterprise solutions architecture. By no coincidence management consultants, systems integrators and solution providers are making millions or tens of millions from these improvement initiatives. 

What value are the asset owners realizing? The exact returns on these investments are often unclear, obfuscated and rarely published in investor presentations and annual reports. Despite research to the contrary, most companies believe what they’ve done is good enough, thank you very much. Nothing to see here. This is fine.

This, of course, impacts Canadian business competitiveness both domestically and globally. It adversely impacts productivity which lowers profitability in private sectors and increases the cost of service in public sectors.

It’s not all bad news. The technology-first approach to organizational transformation in the pursuit of operational excellence has provided infrastructure with tremendous potential. Access to data stored and managed in the cloud has grown exponentially. Analytics tools and platforms offer limitless analysis capability. Now, anything is possible!

Unfortunately, potential doesn’t pay the suppliers. Potential doesn’t pay the shareholders. Potential doesn’t deliver value to other stakeholders like customers, regulators, communities, etc. “Potential is like a summer crop. If it don’t rain, it don’t grow.” – Charles Oakley.

This is a classic case of Field of Dreams – build it and they will come. “Data informs decisions!” we shout. This is precisely where one should question – which decisions exactly? And how? Because that’s where the conversation usually ends.

Our digital transformations haven’t been working because it’s been technology first, people and decisions second. Few initiatives have included an appropriate organizational redesign and new competencies for its people. Fewer changes have been accompanied by revised operating and governance models that complement the new technology. There’s lots of talk about Industry 4.0 but technology isn’t enough when people and decision-making are not adequately supported. We’ve missed the boat on Industry 4.0.

Douglas Hubbard, a risk and decision expert and author at Hubbard Decision Research has asserted, “The most important decision you will make is how you will make your decisions.” This statement is profound in the pursuit of operational excellence as a business outcome. Excellence is an incredibly high bar without room for compromise.

One root cause in underperforming digital transformations is that in the face of massive investment, organizations collectively are still no better at decision-making than they were before the change took place. This is the battleground where operational excellence is won and lost.

Our technology investments have revealed an immediate bottleneck – our people’s capability to ask and answer the right questions resulting in more, better decisions. Data scientists can do almost any manipulation of the data but require capable subject matter expertise to ask and answer the right technical questions with the data and analytical tools. 

It isn’t just the practitioners; leaders are also at fault. What are the key management questions operations leadership is asking of its organization and to what quality are those questions being answered by its practitioners? How are these questions and answers leading to decisions?

What is a decision exactly? It is a choice made under conditions of complexity and uncertainty to meet business objectives.

A decision’s level of structure and rigour applied must be consistent with its degree of complexity and consequence potential. Some decisions are a simple yes/no choice where it is appropriate to use experience and intuition. Other decisions are very complex involving multiple solution options for multiple objectives requiring considerable data and analytical evidence. Good decisions must incorporate not only the best available knowledge but the uncertainty around that knowledge. This is why many decisions should be made with simple quantitative two-pass model frameworks. The first pass gets us into the ballpark while a refined second pass reduces uncertainties associated with the inputs.

There are many questions that should be considered in proper decision-making: What are the important decisions to be made? Who makes them and who is included to provide support? When should they best be made? What knowledge is required? Does knowledge come from experience, data evidence or both? What options, alternatives and scenarios should we consider? What business objectives do we value? How will we balance financial (production revenue, cost) with non-financial (safety, environmental, customer service and quality, social governance and sustainability) drivers? Is this a satisfying decision or an optimization decision? If optimizing, for what and over what period? What if we’re wrong? What are the constraints and can they be tested? What biases exist and can they be minimized? What if we’re wrong? Is the decision reversible? Can we live with the decision if the result turns out poorly?

This structured decision-making technique is rarely utilized.

What’s at stake? A lot. By definition, performance benchmarking allows only 10% of operating companies in the top decile and 25% in the top quartile. These organizations already have good management practices to get them there and believe in continuous improvement to raise the bar even higher. That means the remaining 75% of companies either stuck in the mediocrity of second or third-quartile (or worse) have a lot of work to do to keep up and catch up. The good news is it can be done. McKinsey & Co. say that 10% of companies can actually make the leap to displace an incumbent in the top quartile.

According to Solomon Associates, the difference between average and top-quartile performers can be a 6% increase in production and a 45% reduction in spending. That difference is massive in any organization and is largely due to the organization’s decision-making capacity. Decision management is the key to operational excellence results.

How good is the organization’s current decision-making? Hubbard says it is reflected in the organization’s decision track record. Unfortunately, most organizations are not very good at tracking their decisions, actions, and results. Sadly, many managers would prefer their decisions not to be tracked as the transparency can be uncomfortable. Ultimately, however, decision quality is reflected in operational performance. In the words of W. Edwards Deming, “Your system is perfectly designed to give you the results that you get.

Often the important decisions are obscured in our policies, standards and business processes. Or there is some expectation of some nameless decision to be made with data once analyzed. “Data informs decisions!” we repeat.

There is a principle, an acronym called DIKDAR adapted from data quality management that tells a story. Data > Information > Knowledge > Decision > Action > Result is a progression more than a process. Data by itself is not useful until the technical context is added. This may be done through analysis to synthesize data into information. Information is still not yet actionable until the business context is added to form knowledge. With knowledge, a decision may be made. The decision guides what action will be taken in the form of plans and tasks that deliver a result.

Everyone wants great results. Most people are predisposed to action so once the decision is made, execution is assured to follow so the ‘A’ and the ‘R’ are not the problem here. The key is to make the right decision. Many people will concentrate on the data and information with some notional idea of a decision. This discovery method yields mediocre results. A better way is to centre on the decisions to be made and work backwards. Start with a decision and determine the knowledge required to make the best decision possible at every opportunity. Then determine the information and analytics required to support that knowledge, and finally, determine what data is useful to support the required information. This more deliberate method provides superior results. Some data is more important than other data. The deliberate approach allows the distinction of valuable data to support the decision while the discovery approach does not.

What are the important decisions to be made in operational management? The ISO 5500x Asset Management family of standards provides guidance on how asset owners should coordinate the organization’s activities to create value from its assets to meet the strategic organizational objectives for its stakeholders. These expectations are communicated more practically in the Asset Management Landscape document by the Global Forum for Maintenance and Asset Management (GFMAM.org). This reference clearly and simply outlines the fundamentals of asset management and the 39 subjects of asset management in six subject areas. This set of practices cover the entire asset lifecycle from cradle to grave.

Formal asset management should be foundational for all asset owners but the adoption of this relatively new disciple and emerging profession has been slow globally, particularly in North America. The reason in part for the slow uptake is because of how asset management practitioners have tried to offer and deliver asset management as a heavy-handed standalone documented asset management system that does not integrate well with the asset owners existing operational management.

A more beneficial approach is to cut to the chase, go directly to the important decisions throughout the asset life cycle. Fortunately, there are a finite number of important decision types within those 39 subjects of asset management. A more effective management system framework would codify those decision types and offer a decision model for each enabling the best decision possible at every opportunity. Decision models can be standardized by decision type using simple and proven problem-solving and decision-making methods like the A3 PSDM. Now the knowledge, information and data required to make the best decision are revealed and made obvious. 

An interesting phenomenon happens when the perspective changes from managing the “tasks to be done” to the “what and how decisions are made”. Suddenly the overwrought business process becomes simplified. We no longer need volumes of policy, standards, processes and procedure documents that no one reads (TL;DR – too long didn’t read). Better decision-making can be accomplished with only a modest investment in our people’s competencies and simple tools to consistently make more, better decisions.

Data is the wrong end of the stick. Digital transformations laser focus on data and data management in its technology-led solutions has obfuscated the forest for the trees. Decision management is the right end of the stick. Leaders would do well to center themselves and their organization on more, better decision-making.

Decision-making doesn’t need to be perfect for perfection is not a reasonable expectation. In all decisions made by either commission or omission, there will always be good decisions with good outcomes, bad decisions with good outcomes, bad decisions with bad outcomes and good decisions with bad outcomes. Decision-making simply needs to be better than it was before and hopefully better than peers or competitors to realize more value through continuous improvement.

Digital transformations to date have left operational leaders greatly underserved for the job-to-be-done: to direct the organization’s activities to deliver more value from the same assets with fewer resources. There is a solution. An Enterprise Operational Management System (EOMS) as a simple and effective framework gives leaders the tools to manage, lead and govern the organization.

The EOMS is the lens through which leader see their organization. It is the space where they think about operational performance. It is the canvas upon which they decide where to disproportionately apply its vast and scarce resources. It is how they instruct the organization to act to achieve the desired business outcomes. See. Think. Decide. Act.

Intelligent EOMS design starts with first-principles decision management and also includes systems thinking, human-centred design, modern leadership attributes, choice architecture as well as asset management fundamentals and select operational excellence practices all wrapped in a low administrative burden framework.

The EOMS reframes the wicked problem of value leakage from suboptimal decision-making. It provides the right balance of structure and discipline with flexibility and innovation. It integrates all the activities of the organization to deliver more value than would the sum of its parts. It is built for leaders and first-principles decision-making. As a framework, EOMS fits any organization regardless of maturity or complexity.

An enterprise operational management system is the keystone apex solution that courageous operational leaders in progressive organizations need to manage, lead and govern their organizations. The EOMS is the technology missing from digital transformation projects and the enterprise solution architecture in the odyssey operational leaders are undertaking. Maybe we will get it right in Industry 4.1.

After the digital transformation, operational leaders now need a transmutation of their organization’s decision-making capability. Let it rain to nurture our crops. Step out of the cornfield onto the field of dreams. 

Paul Daoust is the Founder & Managing Director of Scio Asset Management Inc., www.scioam.com.