The agility of an enterprise, the quality of its decisions, its reactive responses to dynamic conditions, its ability to be proactive even in times of internal or external stress, its ability to be reflexive and ethical through objective measures of its own performance, and its ability to innovate derive directly from management’s performance.  Performance can be quantified through the relationships among three metrics: planned  potential, currently capability, and actuality – what you are actually accomplishing.  The relationships work as follows:  enterprise latency is the ratio of capability to potential; enterprise productivity is the ratio of actuality to capability; and enterprise performance is its actuality over its potential.  Echelon 4 engineers the management decision and measurement environment to better monitor and control latency and productivity, improving performance up and down the management chain.

This objective requires management instrumentation and control systems that treat the enterprise holistically, as a tangible entity whose value creation processes are both observable and controllable.  Several decades of applying IT and plant production automation have provided significant increases in productivity.  Yet, our primary measures of performance continue to be a balance sheet and income statement.  These are both valuable tools for measuring historical performance, but neither is a sufficient real-time control tool.  What will power the next gain in expansion and productivity?  In large part, it will be the application of automation and controls science and technology to the upper echelons of management – operations, business development, innovation, and board-level decisions – that will contribute most.  With employing a combination of real-time situation analysis and forward-looking scenarios, proactive managements will be able to steer an enterprise to higher levels of performance.

The greatest improvements in performance will come in domains that remain largely the province of professional management teams.  Today these teams typically function without the advantage of operational business models, nor real-time decision and control resources.  Such technical resources allow operations to self-regulate and adapt, to be autonomic at lower enterprise levels, and thus free management to analyze and develop proactive strategies required for dynamic stability.   Imagine piloting a large ship without the aid of a bridge, an environment where captain and officers meet to plan and control while, in real-time, they monitor the entire operation of the vessel; plot new courses while seeing traffic ahead; and cooperate through the availability of shared instrumentation and integrated automatic controls.

MCSI’s vision and technology are based on a cybernetic  (cybernetics is Greek for steersmanship)  model of the enterprise.  An enterprise is defined as an activity that creates value - for both investors and customers, simultaneously.  Value creation takes place in enterprise systems through allocation and control of capital assets to value production processes (VPU).  Effective enterprise dynamically create and sustain their VPU to operate with agility, speed, economy, and innovation.

The means to more effective management in ever changing technology and capital market conditions involves recognizing the dynamic environment in which VPU must operate.  In one dimension, enterprises are defined by the levels in their corporate accountability hierarchies (aka, org charts, figure 2.)  In another dimension, they are defined by the organization of their management control structure (figure 3.)  And these are often very different things.

• Individual production processes (E1), that are embedded within...
• Direct process controls (E2), that is in turn embedded within...
• Operations [supervisory] controls (E3), that is embedded within...
• Process management functions (E5), with the latter two coupled through...
• Process planning and development functions (E4)

A powerful and valuable aspect of this MCSI view is that the decision and control model applied at each level is the same (figure 4), and is based on the cybernetic principles of "replication" and "semantic recursion".   The principles provide a basis for viability (dynamic stability, homeostasis, adaptability, learning) in living organisms.  As this figure shows, enterprise management encapsulates divisions, which encapsulates business units, and so on down to the shop floor.   Since the management feedback control model is structurally the same at each level, it may be implemented as a "rational object" that is recursively reusable.  Using this recursive model, it is therefore simpler to design, develop, install and commission integrated controls throughout the enterprise.  The basic concept is to use such recursion to treat commercial enterprises as virtually "alive", more adaptive and able to function in environments of continual change.

This perspective views an enterprise as a more autonomic entity and forms the basis of a set of decision and control strategies with the requisite technical (i.e., hardware and software) infrastructure to support them.  This view is supported by the last decade of IT expansion (e.g., MRP, ERP, CRM, intranets, etc.) and the design and capabilities of the present generation of industrial automation (e.g., DCSs and PLCs).  Their respective roles at E1 (device controls) and E2 (process controls) are well understood through large numbers of successful installations, albeit typically in isolated applications.  E3, E4 and E5 controls are the next frontiers for the application of management science coupled with emerging technology.  Based on its particular characteristics, each enterprise will have unique opportunities for developing management and control disciplines.  Echelon 4’s methodologies will identify candidate starting points and logical and pragmatic programs for incremental improvements in performance.

As is well known (cf, Automation Research Corporation), the automation industry is struggling today, and with few exceptions engineering and automation companies have hit somewhat of ceiling in the development of their markets – a barrier defined in part by IT systems and services suppliers, and in part because industrial automation companies themselves are history- and paradigm-bound.  Invensys with Baan and ABB with “Industrial IT” are examples of engineering companies working hard to break through, but they have not achieved much headway against the established systems integrators and IT solution providers.  If engineering companies have been successful in breaking their own paradigms, their customers typically have not.  In large part it is due to the interest of the IT industry to become the purveyors of this paradigm.

IT and engineering companies are, it seems, at a loggerhead and unable to provide their enterprise customers a unified and pragmatically engineered management environment.  Enterprises, at the same time, remain captive of traditional management (e.g., purchasing) modes and organizational behaviors – in spite of decades of implementing IT infrastructure and application tools.  Production shops distrust IT shops, speaking different languages, serving different budget processes, and generally with different objectives and schools of thought.  One reason is that IT practitioners tend to think primarily in terms of hardware and software products, and their value to business process engineering (cf, SAP, Oracle), with focus on resource management systems.  On the other side of the ledger, production organizations tend to think primarily in terms of plant capital equipment and physical production process engineering (cf, ABB, Emerson), with attendant focus on capital equipment management levels.  Neither is fundamentally concerned about modeling, simulation, and control of the enterprise’s dynamic organization – as a system – comprising an embedded, mutually consistent set of engineered and interdependent systems.

Furthermore, IT companies do not typically deal with the design of autonomic (i.e., adaptive, self-regulatory) transactional systems.  To their credit, the engineering companies do; however, they deal with relatively small, highly structured, and statically configured subsets of the overall enterprise dynamics, generally limited to E1.  IBM Research has made public (marketing) statements about commitments to autonomic IT systems, but no clear relationship to enterprise operations has been drawn.  Complex networked computer systems will certainly benefit from more autonomic behaviors (e.g., self-regulation), especially their configuration management (cf, EDS and the DoD’s NMCI Project).  But there still remain at least two or three levels of application systems and process engineering above the computers and their networks that would benefit even more from applied cybernetics.

MCSI  brings the competing views of engineering and IT companies into alignment.

A key benefit of coordinated, holistic operations is transparency – the ability to see the history and the current states of the enterprise, as well as the unfolding of possible futures, at increasingly finer levels of detail.  The means for executives to view operations in this fashion is an enterprise bridge.  Standing on the bridge, management at whatever level of desired control may better steer the enterprise.  The bridge is envisioned as a standard feature of the modern executive boardroom, providing an interactive environment for real-time decision and control.

The design of the bridge, its software in particular, is MCSI product technology.  The platform for the bridge software is standard commercial off-the-shelf (COTS) products.  The communications infrastructure is  COTS internetworking technologies.  As such, the bridge is capable of viewing an enterprise’s global operations, and to be secured using available intranet security features deployed by the enterprise.  In some applications, the source of information required by the bridge services  may need to be developed, but typically the required information is already accessible within existing corporate information systems (e.g., ERP, MRP, CMS, etc.)

Given the current state of the economy and the maturity of computing and communications technologies, the time is right to start removing the obstacles to integrating the transactional IT systems and the production process control systems through enterprise engineering.  And Meta Command Systems is stepping into that breach with experience and valuable professional services, technical architecture, and engineering assets; most cultivated in the automation industry over the last 30 years, all through the eyes of a senior R&D, marketing and technology executive. 

Figure 1 - Enterprise VPU

Figure 2 - Corporate Accountability Hierarchy

Figure 3 - Viable System Model

Figure 4 - Embedded Systems

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