I was listening to Sam Palmisano’s talk on “A Smarter Planet” as part of the Technology and Foreign Policy discussion at the Council for Foreign Relations — the audio version, because I prefer to not sit at my computer to watch the video. He said that as the world gets “flatter”, smaller and more interconnected, the planet is becoming smarter. Smarter means that …
… digital and physical infrastructures of the world are converging.
Three advances in technology are driving this change.
The talk continued with a discussion about how much waste — in energy, gridlocked traffic, supply chain inefficiencies, unsystemic healthcare, and water usage — in the physical world might be reduced through acting smarter. In the pure information world, financial institutions were able to spread risk, but not track risk, which undermined confidence in the markets.
I follow the ideas coming from IBM more closely than most people. I’ve also had the benefit of studying businesses for three decades(!) in various academic contexts. This has led me to reflect on the conjoined ideas on technology and business that have coevolved with me over the past decade. Some significant themes have included:
Formal, historical records of IBM’s directions are clearly documented in annual reports. I’m not an IBM executive, so my academic research is unlikely to impact corporate reports. However, it’s undeniable that my continuing on-the-ground engagements with clients and ongoing conversations with key thinkers inside IBM have shaped the way I see the world. From an academic perspective, I’ve moved closer to Normann (2001) in the view that economic progress is related to technological progress.
The effect of technology is — and always has been — to loosen constraints. As a result of technological development, what was not possible becomes possible. Or what was not economically feasible becomes so. [p. 27]
Each of the four themes are described below. Three themes are historical perspectives. The fourth continues to emerge with my current ongoing research.
For those of us immersed in the world of the Internet, it takes pause to reflect on how much progress has been made over the last decade. The Beloit College Mindset List published in Fall 2008 points out that:
The class of 2012 has grown up in an era where computers and rapid communication are the norm, and colleges no longer trumpet the fact that residence halls are “wired” and equipped with the latest hardware. These students will hardly recognize the availability of telephones in their rooms since they have seldom utilized landlines during their adolescence. They will continue to live on their cell phones and communicate via texting. Roommates, few of whom have ever shared a bedroom, have already checked out each other on Facebook where they have shared their most personal thoughts with the whole world.
In the official IBM history, “network computing” was revolutionary in 1996, and “e-business” was first introduced into vocabulary in 1997 — the same year that Deep Blue defeated Garry Kasparov in chess. The 1997 IBM annual report notes the significance of new language:
… in 1997 … We coined the phrase “e-business” to talk about the value our customers derive from networked computing, to describe how they are reinventing their business models around networked transactions of every kind — among employees, with suppliers, with trading partners, and of course, with customers. [p. 14]
A decade later, I’m still introducing Internet technologies to large enterprises. At home, the average person accessing information for personal uses commonly has the complete world wide web available through a browser, and may be able to authenticate once onto multiple sites using OpenID. In the office, however, it’s still relatively common for information to be siloed in applications: a worker typically has to start up and authenticate with multiple applications separately, for each and every legitimate business function that he or she carries out.
The transformation to e-business is as much about organizations is as it as about technologies. I was fortunate to be assigned to the IBM Advanced Business Institute while Steve Haeckel was writing Adaptive Enterprise. Executives who attended a class at Palisades will usually remember the contrast between operating as bus system (i.e. a production-driven system) and a taxi system (i.e. a service-driven system).
Make-and-Sell Buses versus Sense-and-Respond Taxis
Bus companies are essentially make-and-sell businesses. Using forecasts about where most people will be at different times of the day and where they will want to go, company planners decide the routes buses will take, the stops they will make, and how frequently they will run. Like make-and-sell companies drawing up strategic plans, production schedules, and marketing strategies, bus companies schedule operations that offer the services they expect these customers will need and pay for. Like any good make-and-sell worker, bus drivers must carry out the planners’ schedules as accurately and efficiently as possible. [….]
Taxi companies, on the other hand, share many essential characteristics with sense-and-respond organizations. They hire drivers based on their expectations of how many people have unpredictable transportation needs. They also establish and enforce geographical boundaries, a rate structure, and a compensation scheme. Within that context, however, drivers use their own knowledge, skill, and initiative to get passengers where they want to go. The company dispatches a customer-moving capability. Customers making requests and drivers empowered to fulfill those requests do the rest. Unlike bus drivers, without information from customers about what they need — “I have to be at the airport in half an hour” — taxi drivers cannot perform their service. Only after that request is specified can cabbies put their driving skills and knowledge of city streets and traffic patterns to productive work. [p. 60]
A production-driven business — e.g. a bus operator — can operate without information from its customers. A service-driven system — e.g. a taxi operator — not only requires information from its customers, but can reconfigure its capabilities according to intelligence coming from network partners (e.g. a driver noticing a long queue emerging at a station).
An adaptive enterprise is an e-business. An e-business that takes organizational advantage of its technologies can be an adaptive enterprise.
At the start of the millenium, the attention on transforming enterprises to the e-business vision was limited by focus on Y2K and the dot-com collapse of 2001. Re-emphasizing the challenges of business responsiveness (over technological adoption) was highlighted in the introduction of on demand, as described in the 2003 IBM annual report:
Companies have come to realize that if they’re going to respond rapidly and effectively to today’s volatile marketplace, they need to do more than Web-enable discrete systems, processes or business units. They need to pull together all of the systems they’ve already got and integrate them securely with their core business activities — horizontally, across not just their whole company but their entire value chain, from customers to suppliers. This is an on demand enterprise. [p. 4]
An on demand vision of integrating business functions across organizational boundaries is compatible with the sense-and-respond vision. The involvement of customers and suppliers was reiterated in the 2004 IBM annual report:
On Demand Business is a new way of conceptualizing and managing business activity. It enables companies to achieve higher levels of responsiveness, flexibility and efficiency than legacy Industrial Age business models …. [An] On Demand Business is able to detect and react quickly to changes in supply, demand, pricing, competitors’ moves, shifts in customer preferences and other marketplace dynamics. [p. 16]
During this period, my day job centered on an assignment with Marianne Kosits, initially on the topic of inter-organizational relations, which evolved to become known as relationship alignment. This led to questions about the definitions of management and of governance, which are complementary but distinct in Ing, Hawk, Simmonds and Kosits (2003).
Management, as a practice, traditionally is oriented more to setting direction
Management is derived from the mid-16th century Proto-Romance maneggiare, from a Latin root of manus (hand). A constructed definition then describes management as:
the general manner or specific action of applying skills or care in the manipulation, use, treatment, or control of things or persons, as in the conduct of an enterprise, operation, etc.
Its original sense comes from the French, who “encouraged” horses through the use of hands, carrots and sticks to perform in ways that served the trainers, but were not natural for the horses. [p. 8]
Governance is usually oriented towards setting and enforcing bounds
The Oxford English Dictionary (OED) presents governance as derived from the Latin word gubernare (to steer, direct, or rule), as well as the Greek kubernan (to steer). A definition for governance can then be composed as:
the general manner or specific action through which a social body is guided, directed, steered or regulated.
In this definition, the phrase “social body” tends to rule out governing an individual person or things. Normally, governing involves a group of people, rather than a single person. [p. 9]
In a transformation to become an on demand business, the nature of governance may change more than the nature of management. Two or more organizations may form an alliance to pursue a common direction of interest. The challenge is generally less in the directions that have been decided mutually than on the boundaries for actions that are often implicit and predisposed from the cultures of organizational origin. Ambiguity about shared direction is usually explicit, whereas boundaries for the emergent or unpredicted are often undiscussed. Since business people have generally had less experience with network-form organizations, negotiated order is likely to form a larger part of the shared context.
In 1962, Thomas J. Watson codified three basic beliefs for IBM: respect for the individual, customer service, and excellence. The basic beliefs were complemented in 2003, with a declaration by Sam Palmisano of values based on three principles:
The principle of innovation that matters was associated with a re-examination of the meaning of innovation. IBM conducted its first Global Innovation Outlook in 2004, distinguishing innovation from invention, and redefined innovation for the 21st century on the premise that:
… innovation itself is changing in at least three major ways. [p. 4]
one: It is occurring more rapidly — barriers of geography and access have come down, enabling shorter cycles from invention to market saturation.
two: It requires wider collaboration across disciplines and specialties — where until recently, people hunkering down in a garage could create a new technology that would sweep the world, many challenges are now too complex to be solved by individual pockets of brilliance, let alone brilliant individuals. Combinations of technologies, expertise, business models and policies will now drive innovation.
three: The concept of intellectual property is being reexamined in the light of these collaborative demands. Increasingly, entities that treat intellectual assets more like capital — something to be invested, spread, even shared to reap a return, not tightly con-trolled and hoarded — will find the clearest paths to success. [p. 5]
The first GIO was followed by a second version in 2006 and a third version in 2008. The one-word slogan — THINK — originating in the 1920s from Thomas J. Watson, Sr., reappeared in a refresh context in the 2006 IBM annual report:
… when you commit yourself to innovation that matters, you free up talented people to try new things — new approaches, new partnerships, new markets. That is, you ask them to think. [p. 9]
The 2006 annual report was bundled with a complementary book, THINK, that described a world of complex systems:
Our world is made up of complex systems. [p. 1]
To extract their full potential, you have to understand how they work in all their dimensions. [p. 9]
To advance healthcare, it’s not enough to discover new medicines, assess risks, pass legislation, or promote wellness. As with any complex system, you need to analyze how work flows, how people interact and how processes can be more productive and human. [….] [p. 15]
A river is a system. [p. 22]
Energy is a system. [p. 24]
Your company is a system, too. [p. 27]
In this period, I led development of a curriculum in a Master’s Program in International Service Business Management at Helsinki Polytechnic Stadia. This coincided with the rise of the Services Science, Management and Engineering initiative from the IBM Almaden Research Center in general, and the “Services Science, Management and Engineering — Education for the 21st Century” Conference in October 2006 in particular. As the writing on SSME has matured, I was happy to see the convergence of SSME ideas and systems ideas into the science of service systems, first in Spohrer, Maglio et al. (2007), with the final refinement in the University of Cambridge IfM and IBM 2008 report:
What is a service system?
A service system can be defined as a dynamic configuration of resources (people, technology, organisations and shared information) that creates and delivers value between the provider and the customer through service. In many cases, a service system is a complex system in that configurations of resources interact in a non-linear way. Primary interactions take place at the interface between the provider and the customer. However, with the advent of ICT, customer-to-customer and supplier-to-supplier interactions have also become prevalent. These complex interactions create a system whose behaviour is difficult to explain and predict. [p. 6]
I personally sorted through definitions for a science of service systems, service sector and service economy — in ways that may or may not be consistent with viewpoints of other researchers. I see agricultural, industrial and service primarily as paradigms, rather than as sectors of the economy.
This meander through the past decade of ideas now brings us to the current statement that digital and physical infrastructures are converging. In an exercise with “instrument, interconnected, intelligent” in the right column, consider what alternative antonyms for the left column might be. Here’s my attempt:
|Pre-digital physical infrastructure||.||Converging digital and physical infrastructures|
|World as invisible or unobserved||.||World as instrumented|
|Analog / synchronous connections,
person-to-person and machine-to-machine
|.||World as interconnected|
|Things as dumb or unresponsive to interaction||.||Things as intelligent|
The smarter planet talk by Sam Palmisano gave some examples of infrastructures: supply chains, healthcare networks and cities. In a pre-digital world a package could only be assumed to be on a truck, from the time it had left one shipping dock, until the time that it had been physically counted into the receipts at the destination. Similarly, the operation of a medical device, e.g. a hearing aid, would be checked only on visits to the health specialist or when the patient sensed dysfunction. Durable urban infrastructures, e.g. road and waterways, have typically only been inspected periodically for stress, or after signs of failure are pointed out. In a converged digital and physical infrastructure, the package, hearing aid and road can be constructed to monitor itself and send out an alert when a parameter is detected beyond a desired specification.
A world that is instrumented actively provides a continual stream of measurements. Without that active monitoring, those parts of the world are invisible or unobserved, as a tree falls in a forest with no one to hear it.
A world that is interconnected enables data and information to effortlessly flow and be applied in productive contexts, possibly beyond its originally designed purposes. Without reliable information interconnections, human beings serve as bridges: filling in contexts and storing subjective memories. While direct machine-to-machine interconnections are not a substitute for wisdom, the combination of observations from multiple devices can provide some consistency in objectivity.
Things that are intelligent can be programmed to selectively transmit varying sets of information to different receivers. Continual data streams encourage real-time alerts and action, when the receiving computer can process information at a rate faster than it arrives. In a data-rich environment, the constant arrival of fresh indicators eventually strains storage capacities, leading to archiving and/or data reduction procedures. A pre-digital infrastructure is unaware of its state, and has to be observed by something or someone outside itself.
I recently attended the SysML Information Days, co-sponsored by the Object Management Group — a computer industry standards group — and the International Council on Systems Engineering (INCOSE) — a professional membership organization of systems engineers. The development of SysML — Systems Modeling Language — has followed an interesting and productive path. As an alternative to defining yet another modeling language, systems engineers built on the work of software engineers. Unified Modeling Language (UML) specifies the structure, behaviour and interactions of software systems. The language is independent of methods, so that different approaches to analysis, design and implementation of a system are possible.
To this point, software modelers have often used UML to model non-software domains. With the approval of the final specifications for OMG SysML 1.1 on October 15, 2008, systems engineers can model physical infrastructures in SysML in a way that is highly compatible with software engineers modeling digital infrastructures. This is leading me to look into system of systems (e.g. services from a system of systems perspective, and system of systems engineering management). The intersection of digital and physical infrastructure in a system of systems perspective is just beginning.
Stephan H. Haeckel, Adaptive Enterprise: Creating and Leading Sense-and-Respond Organizations, Harvard Business School Press, 1999.
Alex Gorod, Brian Sauser and John Boardman, “System-of-Systems Engineering Management: A
Review of Modern History and a Path Forward”, IEEE Systems Journal, Volume 2, Number 4, (Dec. 2008), pp. 484-499, http://dx.doi.org/10.1109/JSYST.2008.2007163
Ifm and IBM, Succeeding through Service Innovation: A Service Perspective for Education, Research, Business and Government, University of Cambridge Institute for Manufacturing, Cambridge, UK, 2008, http://www.ifm.eng.cam.ac.uk/ssme/
David Ing, “Business Models and Evolving Economic Paradigms: A Systems Science Approach“, Proceedings of the 52nd Annual Conference of the International Society for the Systems Sciences, (Jennifer Wilby, editor), presented at the University of Wisconsin, Madison, July 16, 2008.
David Ing, David Hawk, Ian Simmonds, and Marianne Kosits, “Governance and the Practice of Management in Long-Term Inter-Organizational Relations“, Proceedings of the 47th Annual Meeting of the International Society for the System Sciences at Hersonissos, Crete, July 7-11, 2003.
Richard Normann, Reframing Business : When the Map Changes the Landscape, Wiley 2001.
Annaleena Parhankangas, David Ing, David L. Hawk, Gosia Dane, and Marianne Kosits, “Negotiated Order and Network Form Organizations“, in Systems Research and Behavioral Science, Volume 22, Number 5, (October 2005), pp. 431-452, http://doi.wiley.com/10.1002/sres.717
Jim Spohrer, Paul P. Maglio, John Bailey, and Daniel Gruhl, Steps Towards a Science of Service Systems, Computer, volume 40, number 1, (2007) pp. 71-77, http://dx.doi.org/10.1109/MC.2007.33
James M. Tien, “Services: A System’s Perspective”, IEEE Systems Journal, Volume 2, Issue 1, (March 2008), pp. 146-157, http://dx.doi.org/10.1109/JSYST.2008.917075
daviding December 30th, 2008