Defining Enterprise Information Value
Let's say that an enterprise is a complex collection of semiautonomous units that share some common goals. An Enterprise Information System (EIS), then, is a distributed, networked, set of information processing nodes that services the units of the enterprise, and especially information transactions across the units.
This concept of EIS is highly scalable by definition. An arbitrarily large and growing set of processing nodes might comprise an Enterprise Information System of Systems. A processing node might be a microprocessor or a super computer. Subsets of EIS nodes comprise subsystems or components. The ability to rapidly compose systems from components, and systems of systems from systems, is a central value attribute of an EIS. Accordingly, the design of an EIS must be “open” to the extent that it allows member units of the enterprise to autonomously expand and federate horizontally.
The Value Assurance Framework (VAF) aims to improve the predicable level of global success at developing large EIS. VAF is based on close observation of many success and failure cases, and includes artifacts that capture reusable, practices that have proven to be effective for designing, building, validating, verifying, certifying, maintaining, and operating EIS.
Among other definitions, Merriam Webster’s first definition for value is “a fair return or equivalent in goods, services, or money for something exchanged.” In this sense, “value” is different than “cost.” “Value” is perceived worth, perhaps in terms of money, but not necessarily.
Possession of a product or service sooner rather than later is often valued. Similarly, the value of product or service usually changes over time. It might increase (wine, antiques, tickets as the event approaches) or, decrease (used cars, electronic equipment, out-of-style clothing) over time.
Value is often measured in terms of the effect of the procured product or service, e.g. time saved, pain reduced, pleasure achieved, productivity increased, i.e. utility. The first definition of “utility” in the online Oxford dictionary is “the state of being useful, profitable, or beneficial.” Hence, customer requirements are closely related to utility. Indeed, if the customer values the utility delivered, then the customer’s requirements must have been satisfied, by definition. This definition of utility is also consistent with the economic utility theory. For example, the Neumann & Morgenstern Utility Theorem explains mathematically how “rationale actors” will invest in ways that maximize the probability that they will achieve desired outcomes, but with due consideration of appetite for risk and subjective preferences.
Cost is the price of the utility delivered, perhaps in monetary terms, but not necessarily. Costs might also be measured in terms of time. Cost can also be associated with opportunity, i.e., the customer could have bought something else, and/or the producer could have delivered something else.
Value depends on utility, cost, and time.
In business, a consumer’s objective is to receive maximum utility-per-cost. A provider’s objective is to maximize the margin between the consumer’s perception of utility, measured in terms of the price she is willing to pay, and the cost to produce or provide a product or service. In either case, best practices evolve around ability to increase the perceived margin between costs (including production time) and utility delivered.
|IT is evolving so quickly and unpredictably that it makes sense to manage risks like the most successful financial portfolio mangers. VAF maps traditional acquisition artifacts and processes to the investment portfolio metaphor.|
As in any other business, the objective of an EIS provider-consumer ecosystem is to focus processes and tools to produce more perceived customer utility, faster, at lower production costs. That is, the EIS business objective is to create and continuously evolve a value delivery chain. Note that “value delivery chain” is a well-developed industrial concept. Trademarked processes for developing customer-centric leading and lagging metrics designed to optimize enterprise value delivery chains continuously evolve. Examples include Lean, Total Quality Management (TQM), Six Sigma, ITIL, Business Process Management (BPM), and Scrum.
|VAF is informed by a broad baseline of research, analysis, tools, and literature. VAF captures recurring best practices in reusable templates.|
Ultimately, the purpose of an EIS is to deliver value-added information. Information is useful if (and arguably only if) it leads to better decisions. A decision might be as mundane as which movie to watch, or as critical as whether or not to launch a missile at one target or another. Regardless, measures of utility in this regard should address the confidence in, and quality of, the decision supported.
The concept of utility is more abstract than the concept of cost or time. That is, it can be difficult to quantify utility while costs and time are much easier to measure. For example consumers value convenience as a utility. What is the unit of convenience? It might not be impossible to quantify convenience per se. On the other hand, time-and-effort-avoided are essentially equivalent to convenience. Time saved by making mouse clicks instead of trips to the shopping mall, or by automatically downloading data instead of entering it manually, is measurable.
Consumers value confidence and quality. For example they want certainty (confidence) that they are choosing good cost options from among the many available alternatives of varying merit (quality). Confidence and quality are not always directly quantifiable, but there are viable proxies. For example, various consumer guides use number-of-stars as a indicators of confidence and/or quality. Stars can be keyed to measurable quality factors such as security, reliability, safety, timeliness, or performance in some cases. Sometimes, even though the number of stars is ostensibly objective, that number is keyed to subjective opinions of (hopefully) trusted evaluators. In both cases, star assignments that are backed up by trusted logos (certifications) such as Consumer Report, Underwriters’ Labs, National Institute of Standards (NIST,) or Oprah’s Book Club, make the star ratings more trustworthy.
VAF defines utility of delivered information, as its worthiness to support a critical decision by increasing confidence in achieving desired outcomes. Critical decisions include especially changes to planned courses of actions, or allocation of resources to initiate new courses of action. Under this definition, leading measures of information utility would likely include combinations of information timeliness, breadth of data surveyed, pedigree of data surveyed, security, relevance, and reliability. Utility might also include the concept of surprise, i.e. discovery of important new insight. In this sense, information that provides new perspective or insight, i.e. a new worldview, is significant. Significant information provides more utility than information that is merely relevant. Proxy measures for significance are the same Measures of Effectiveness (MoE) used to quantify targeted operational outcomes. If delivered information enhances MoE, then the delivered information must have been significant, i.e. had high utility.
VAF uses objective measures of desired EIS outcomes, e.g. probability of good or bad outcomes, proficiency scores, latency, reliability, accuracy, availability, etc., as proxy measures of EIS utility. Choosing these metrics carefully, and properly defining their enterprise interrelationships to manage risks are critical to EIS success.