The Hindu Business Line : Enterprise Management — Building intelligence into information systems

Knowledge Management, which is the orderly encapsulation and deployment of critical knowledge, is vital in fostering a firm's competitiveness. Enterprise Management Systems provide a management and technology framework for superior Knowledge Management.

Enterprise Applications (enterprise resource planning, supply chain, customer relationship management, and the like), coupled with business process redesign, are a part of the IT and corporate firmament worldwide. Enterprise Applications are not used just to computerise ways of doing business, but as drivers of the change business corporations must undergo to compete successfully in the information age.

New versions of Enterprise Applications do not limit transformation to individual business corporations. Equipped with powerful adjunct capabilities such as Composite Applications and Service-Oriented Architecture (SOA), they are making wholesale changes to the entire supply chain: suppliers, suppliers' suppliers, customers and customers' customers. The complexities of implementing these packages and the consequent obsession with data management have led many to believe, incorrectly, that there is no life after Enterprise Applications deployment.

While the power of Enterprise Applications is awesome, it falls short of supporting the most vital tasks of management. Sooner than later, business corporations will migrate from mere data management to sophisticated knowledge management efforts. Such efforts will result in a set of powerful information systems called Enterprise Management Systems (EMS) that will be a legitimate sequel to Enterprise Applications.

Task of management

Many management thinkers, including Peter Drucker, have presented diverse models to describe the task of management. But none argues the case more cogently than the Shewhart Cycle, known better to the world as the Deming Cycle. The Deming Cycle was originally proposed by Walter Shewhart and popularised in Japan by Edwards Deming after which it came to be known as the Deming Cycle. The Deming Cycle, shown in Figure 1, sums up the task of management as a closed loop activity system.

The four principal steps in the Deming Cycle are:

Plan: Define the destination you are aspiring for. The destination could be that of the enterprise, of a business process or of a small team. Using appropriate techniques validate that this destination is worthy of reaching. Generate alternative ways of reaching the destination and choose one.

Do: Carry out the plan of action. The plan is implemented in one or more business processes.

Check: Using appropriate measurement systems determine if the destination was reached. If you did, go back to generating fresh plans.

If not, move to the next step, Act.

Act: As in the Plan step, except for being informed by the results from the Check step, generate alternatives to close the gap between the current state and the destination. Migrate to the Plan step to add plans for new initiatives.

The endless repetition of this P-D-C-A cycle constitutes the task of managing and running the business enterprise.

The Deming Cycle is a fractal. One cycle spawns others. The actions emerging out of the `Do' step at a higher level of abstraction become the contents of the `Plan' step of the next lower level. For example, the `Plan' of increasing market share at one level may spawn a `Do' step of running a media campaign with a designated effectiveness. This becomes the content for the `Plan' step of the business process that will implement the campaign. Thus the fractal chain is used at practically all levels in the organisation: Corporate, business unit, business process or individual.

The Deming Cycle can be applied equally to a strategy or an operations problem. It can, for example, be applied to the operational problem of cutting down the cycle time of the new product development process. It can be applied equally to the strategic problem of gaining market share by the addition of new features to a product that would change its positioning in the marketplace.

Role of Enterprise Applications

The domain of Enterprise Applications is primarily the `Do' and `Check' steps. For the greater part, ERP implementation has been an "equalising" effort rather than a "differentiating" effort. A handful of discerning enterprises have used the strength of ERP with the power of Business Process Redesign to develop signature processes that lead to a distinct competitive advantage.

Business Intelligence extensions to Enterprise Applications, performance measurement systems and their ilk assist management with the `Check' step.

Retrospective Analytics work more at the `Check' step than at the `Plan' or `Act' steps to provide discernible patterns that might account for the gap between actual results and the goals evolved during the Plan step. The emergence of Predictive Analytics is providing the first glimmer of substantive assistance to managers, both at the Plan and Check levels. Yet Predictive Analytics is incapable of using expert rules and heuristic reasoning.

It is evident from Figure 1 that today's Enterprise Applications concentrate on the Do and Check steps and offer scanty support for the Plan and Act steps. Therefore, IT-enabled management is still not a closed-loop system. However, the proposition of Enterprise Management Systems (EMS) will permit the installation of a powerful, revitalised Deming Cycle.

Enterprise Management Systems

Enterprise Management Systems (EMS) are intelligent information systems that embed specialist components to support the `Plan' and `Act' steps (see Figure 2). An EMS consists of three principal components:

Enterprise Applications (Transactions) that contain data relating to the thousands of transactions by which an enterprise conducts its business Enterprise Applications (Business Intelligence) that incorporate the power of both Retrospective Analytics and Predictive Analytics that reveal patterns, both past and prospective, contained in the transaction layer

Enterprise Planning Systems (EPS) that contain the knowledge base and the inference mechanisms which act upon both transactions and patterns to generate alternatives for the `Plan' and `Act' steps.

EMS help management teams continuously evolve plans at the various levels of management, such as corporate, strategic business unit, and business process. They support the P-D-C-A fractal evolution and make IT-enabled management a closed loop.

The process of generating `Plan' and `Act' steps has to be understood from a computational and reasoning perspective. Computational sciences, in general, and Artificial Intelligence (AI), in particular, have dealt with planning as state transition. The Plan and Act steps deal with the transition from the current state to a desired state.

For example, in the new product development process, the current state of the process could be a cycle time of 130 days. The desired state could be a cycle time of 80 days. The Plan step, using the knowledge repository and inference mechanisms of EPS, would generate alternatives for transitioning from the current state (cycle time of 130 days) to the desired state (cycle time of 80 days).

These alternatives are implemented in the form of business transactions by Enterprise Applications (in this case, perhaps a PLM application). The Check step determines whether the desired state (actual cycle time of 80 days) was achieved. If not, the Act step, enabled by appropriate EPS components, generates a set of alternatives to close the gap. At the heart of EPS would be knowledge representation schemes, inference mechanisms, search strategies and heuristic reasoning mechanisms.

The need for EMS is now being filled by manual, cumbersome and unreliable methods. Most often the success of reasoning is dependent on a few experts and intuition. Some smart companies have written bespoke applications that perform the function of EMS, but are finding such applications incredibly difficult to maintain and grow.

The EMS architecture and EPS in specific will draw significantly on techniques of AI and computational sciences. There has been some disappointment in the industry with the use of these techniques in the not-too-distant past. With Enterprise Applications acting as a solid bedrock of data, elegant user interfaces, and the dramatic reduction in the cost of computing with an equally dramatic rise in computing power, there is a strong case for revisiting extant assumptions and feelings about intelligent search and planning techniques.

Knowledge Management

Clearly data management now is a victim of the law of diminishing returns. New incremental investments in data management are returning less and less. The competitive differentiation offered to early adopters of Enterprise Applications has been all but eliminated. True competitive advantage consists in the intelligent management of a corporation's specific problem-solving knowledge that gives it an edge. The manufacturing efficiencies of Dell, the management of cost per seat-mile of Southwest and Wal-Mart's supply chain management knowledge, empowered by technology, give them their competitive advantage — not run-of-the-mill Enterprise Applications.

Knowledge Management, which is the orderly encapsulation, perpetuation and deployment of such critical knowledge, is vital to foster a firm's competitiveness. Enterprise Management Systems (EMS) provide a management and technology framework for superior Knowledge Management.

(The author is Founder and CEO of Anantara Solutions Private Limited. TM Enterprise Management Systems (EMS) and Enterprise Planning Systems (EPS) are trademarks under application by Anantara Solutions Private Limited.)

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