RAILWAY AGE, DECEMBER 2022 ISSUE: This is Part 1, “From Sensors to the Boardroom,” of a three-part series based upon our new book, Dynamic Multi-Level Decisioning Architecture: Making the Right Decisions at the Right Time, With the Right Authority for Sustained Competitiveness and Relevance. It’s about how all industries, including the rail industry, its partners and adjacent competitors, are evolving in the throes of digital disruption and other external forces, and the role people play in decision-making at all levels of an organization. Decision-making needs to flow better upwards and downwards, tying the boardroom to the railroad yards, transloading facilities, tracks—the whole rail network and transportation ecosystem.
The bigger story is about each stakeholder needing a better understanding of how to make the right decision at the right time with better, more-focused knowledge, applying hard-earned wisdom to make better decisions with better and traceable outcomes. It’s about the convergence of two long-standing silos, OT (operational technology) and IT (information technology), becoming the cornerstone of effective innovation in large, complex firms like railroads, which need to meet the increasing impact of disruptive forces. The need to address this convergence affects a wide range of disciplines to unveil a much broader scale of end-to-end systems—from the sensors in the field to the boardroom. Out-of-date, isolated data that lacks context causes major paralysis.
Wisdom is needed for managing the exponentially increasing complexity gap organizations face. It means seeing within the context of systems and root causes. Real-time decision-making becomes possible from the sensors on the ground sending to the boardroom data transformed into information yielding knowledge, while accounting for the unpredictable external forces and the internal realities that organizations face. This approach provides senior executives with ability to understand the effects that their decisions have on their organizations in a much shorter timeframe, rather than the typical several quarters.
Decision-making in today’s environment needs to be reexamined. Organizations are subject to forces that require some form of response and require a change in how they operate. They include market, technological, economic, ideological, moral, ethical, legal, regulatory, political, governmental, psychological, sociological and environmental. Most organizations are dynamic and respond to change. However, disruption to business models is rapidly increasing, especially from new technologies. The ability to confidently respond to this increasing wave of change requires reimagining how decisions are enabled. If a company only needs to learn to master one thing, then learn to master decision-making.
Decisioning systems are making a real comeback because they can be made more practical and easier to use. The data that these systems consume is increasing dramatically. Operational information technology convergence—OT/IT convergence—is the cornerstone that enables making the right decision at the right time with the right level of authority and scope. Executives must ask if their strategic and tactical objectives are being translated into the right actions through all the layers of management and operations with the right impact. The question facing leadership is how to create a virtuous cycle of relevant decision-making from the boardroom to the ground level and all the levels in between. This requires a timely and meaningful feedback loop to understand if the executive decisions are making a crucial difference. Those carrying out these decisions need to know that they have the right information to meet the objectives. Real-time insight changes every aspect of decision-making from the boardroom to the ground floor. Leveraging exponentially increasing information and knowledge interconnects suppliers and partners and consumers and even disruptive competitors. It transforms the ecosystem.
This opportunity is not free and it’s not easy, especially for long-established companies with an aging infrastructure and an aging operations portfolio that have technical debt. There’s also something called enterprise debt or enterprise drag. The real question is, do organizations respond fast and effectively enough in the right areas with the correct investments?
We’ve all heard and experienced “analysis paralysis,” which emerges from the fear that information and knowledge available to make informed decisions is lacking, contradictory or stale. This creates uncertainty that ranges from the ground through every layer of management as it rolls up to the boardroom. Most organizations have invested heavily in all manner of analytic and data-gathering capabilities. Imagine the frustration they feel when they have those results and wonder why what they’ve spent doesn’t add up yet.
Economic and business conditions are driving shippers to use more modes and more complex routing scenarios across geographies and various regulations. Meanwhile, the carriers typically focus on their internal sphere and often are unaware of the impacts they have downstream or at their handoff points. End-to-end delivery goals become fragmented, and this increases the risk of not meeting obligations and achieving business goals. This fragmentation highlights the importance of supply chain execution and convergence, and the ability to work together across functional domains such as merchandising, transportation, warehousing and manufacturing.
A key element of the solution is a real-time decisioning framework that incorporates secure digital twins for mediating OT/IT convergence while also leveraging the myriad of new technologies like AI, machine learning, multi-cloud and IoT (internet of things). Coupled to this is the Business Environment as a Service (BEaaS) platform, where providers and consumers participate in building and evolving an ecosystem over time and where they benefit by providing and consuming the services. It’s a control system with an active feedback loop that presents the opportunity to control chaos. Organizations can assign varying levels of authority to effectively execute what needs to be done to sustain their competitiveness. Staged investment in these technologies can be strategically introduced so that subsequent phases can be paid for by savings obtained in prior phases.
For example, in a transload facility, unpredictable forklift failures are a bottom-line cost. However, workflow interruption affects top line revenues and incurs reputational loss. Top line impacts are even greater and more significant than bottom line costs. Using sensor-equipped forklifts as input for promoting an analytics-driven decision culture extends data and information through to knowledge, wisdom and useful insights. You can apply the same principles to locomotives. Each equipment category has its specific idiosyncrasies, but predictive analytics, safety and maintenance principles apply universally. For example, you can use the same machine learning equation to predict mishaps using asset-specific parameters for highways or railways.
Another example: The rail industry has defined five stages for autonomous vehicles globally. Most industries are in the early stage two of automated vehicle maturity. Humans must be very diligent, especially in poor weather conditions or heavy pedestrian and vehicle traffic in urban areas. Autonomous vehicle manufacturers do have one top competitive priority: achieve as close to level five autonomy as possible. This is a long, hard road, and railroads need to work with what they can do safely. They may not be cutting edge in some cases. Some of the challenges are real-time handling of vehicle health and supporting autonomous systems. The vehicle must understand and react to changing conditions in milliseconds. This requires a large deployment of sensors and cameras to capture and transmit data in nanoseconds. The processing capacity to interpret these diverse sets of data streams has to be very large and will keep growing. Prediction and reaction algorithms must leverage the established wisdom of prior situations, such as roadworker protection. All of this must be placed in the context of how to invest in a strategy that creates the opportunity to continually stay ahead of your competition.
Railroads represent a classic example of vertical and horizontal integration. The former has long been the choice to boost economies of scale. The current state of disruption raises questions about how effective heavy vertical integration will be going forward. When niche players are entering from adjacent markets to provide services and products that are highly specialized, they also can pivot their offerings very quickly due to their smaller sizes. This is especially significant when one considers that the startup costs of innovation have dropped precipitously, allowing more adjacent startups to enter the market. These players can eat away at your competitive advantage slowly without getting noticed until it’s too late. That’s why horizontal integration is a strategic advantage, and why focusing on the core business is what will win the day.
Information tends to get buried in spreadsheets or crammed into slide decks and PDF reports. Occasionally, some messaging massaging is done so that a bit of knowledge can be gleaned by decision-makers. The final step is often hard to accomplish. A large gap exists between the use of information and the creation of knowledge that decision-makers can apply to leverage wisdom. But with the emergence of feasible machine learning and use of rich graphing techniques and advanced visual rendering, the era of knowledge-centric decision-making has been maturing over the past decade. Effective use of this technology is becoming a competitive advantage. The need to bridge the gap with greater speed is a vital step in creating sustainable sets of services and products that fend off unexpected competition.
Wisdom is earned through life experience. The largest impact wisdom provides is hard decision-making, amid pervasive ambiguity where information is not only incomplete, but also possibly contradictory. Wisdom is knowing how to handle ambiguity, recognizing and managing the multiple possible outcomes from a set of operational events. Knowledge alone will not be able to uncover the latent needs of the key stakeholders—employers, customers, clients, suppliers and partners. Wisdom integrates the values and cultures of an organization, especially as it relates to its tolerance for change. It requires changes to processes and skills, while employing a safety net for people.
We really need to integrate wisdom and insights in real time. This is a gap that organizations need to close, particularly as they modernize their architectures in the push for digitalization of businesses. We strongly encourage people to overcome the bias to status quo inertia in their organizations. This is important because the next disruptor may not be obvious before it’s too late, and you are left behind irrelevant and unprofitable.
Sonia Bot, chief executive of The BOT Consulting Group Inc., has played key roles in the inception and delivery of several strategic businesses and transformations in technology, media and telecommunications companies worldwide. By utilizing methodologies in entrepreneurship, business precision, Lean Six Sigma, system and process engineering, and organizational behavior, she’s enabled organizations to deliver breakthrough results along with providing them a foundation to continue to excel. Sonia’s contributions to the rail industry are as a leader and a visionary who is passionate in taking railroading into the next generation. Within the Digital Business Transformation context, she leads high-stakes mandates where new business models are created and enabled by digital technologies. She was instrumental in PTC implementation on CN’s U.S. lines. Her approaches on the evolution of railroading and transportation are game-changers that drive innovation and competitive advantage for adopters in a changing industry. Sonia can be reached at [email protected].
Sheppard Narkier, a CTO and Senior Enterprise Architect, is routinely tasked with complex, difficult transformation projects in a range of industries including demanding Capital Markets environments. Sheppard was recruited into 11 unique roles including Chief Technical Architect at a global investment bank, CTO of a global consultancy, and Chief Scientist at a startup. He has defined the architecture and rules systems for several application and infrastructure design platforms resulting in seven awarded patents. As a facilitator of change, he has driven the organizational transformations aligning systems development structures, processes, and data repositories with their strategic goals. A pioneer in cloud strategy, he developed IP in several companies to guide enterprises toward staged migration to hybrid multi-cloud across a range of horizontal and vertical scenarios. He has also employed multidisciplinary Design Thinking in recent engagements. Sheppard can be reached at [email protected].
David Sherr is in his sixth decade as a practitioner, thought leader, and executive in entrepreneurship, system design and development, and enterprise architecture. He has worked in six world-class financial institutions where he held CTO and VP positions and consulted in technology strategy for Fortune 100 companies. Currently, David is heading an IoT startup to build predictive maintenance analytics for industrial assets. As an inventor, he is named on six patents covering enterprise data management, Web services architecture, IoT Digital Twins, and, most recently, software-designed network resource provisioning architecture. David can be reached at [email protected] or www.newglobalenterprises.net/SCA.