Operational business intelligence (BI) has a focus on day-to-day operations and so requires low-latency or real-time data to be integrated with historical data. It also requires BI systems that are integrated with operational business processes. However, while operational BI might be part
and parcel of operational processes and systems, the focus is still on changing how people make decisions in an operational context. To compete on decisions, however, you must recognize that your customers react to the choices made by you, your staff and your systems, and that you must manage all the decisions you (or your systems) make – even the
very small ones. This is the basis for enterprise decision management or EDM. Five main areas of difference exist between operational BI and EDM – a focus on decisions (especially operational
ones), organizational integration, analytic technology change, adoption of additional technology and adaptive control.
In this article, I want to outline some steps organizations can take as they move from “traditional” BI towards operational BI and enterprise decision management. Some of these steps would be a good idea if operational BI was your goal. But hopefully you are more ambitious than that and want to really begin to compete on decisions.
Fundamentally, Web 3.0 is about using semantic technology to derive meaning from the vast accumulation of textual information out there on the Web and do something useful with it. If you want a slightly deeper dive on Web 3.0 then read What is Web 3.0 and Why Should I Care? but fundamentally it’s about semantic technology.
Pysdex uses such technology to parse information in real time for meaning, aggregating it and filtering it, and delivering it to various streamed services that it offers to its customers. The diagram below illustrates that process.
Unlike traditional BI, an operational BI system should be focused on influencing the interaction with your customer to provide benefit to both the customer and your business. Traditional BI, while often seen as a tool with a very fuzzy ROI, is nonetheless necessary for conducting business. Operational BI, on the other hand, provides a much clearer benefit because it directly addresses your business.
1. Decisions are the unit of work to which BI initiatives should be applied.
2. Providing access to data and tools isn't enough if you want to ensure that decisions are actually improved.
3. If you're going to supply data to a decision-maker, it should be only what is needed to make the decision.
4. The relationship between information and decisions is a choice organizations can make--from "loosely coupled," which is what happens in traditional BI, to "automated," in which the decision is made through automation.
5. "Loosely coupled" decision and information relationships are efficient to provision with information (hence many decisions can be supported), but don't often lead to better decisions.
6. The most interesting relationship involves "structured human" decisions, in which human beings still make the final decision, but the specific information used to make the decision is made available to the decision-maker in some enhanced fashion.
7. You can't really determine the value of BI or data warehousing unless they're linked to a particular initiative to improve decision-making. Otherwise, you'll have no idea how the information and tools are being used.
8. The more closely you want to link information and decisions, the more specific you have to get in focusing on a particular decision.
9. Efforts to create "one version of the truth" are useful in creating better decisions, but you can spend a lot of time and money on that goal for uncertain return unless you are very focused on the decisions to be made as a result.
10. Business intelligence results will increasingly be achieved by IT solutions that are specific to particular industries and decisions within them.
An agent capable of general intelligence approximates the
knowledge level on an
unbounded set of problems with little inherent knowledge of the domain.
The capabilities needed to support general
intelligence are not generally known (although many have been
empirically determined
to be of significant importance; e.g.,
learning)
Additionally, no theory exists for determining either the
necessary or sufficient structures needed to support particular capabilities
and certainly not to support general intelligence
(although see
Unified Theories of Cognition for work in
developing such theories)
Business Process Management (BPM) und Business Rules Management (BRM) zusammen in einer service-orientierten Architektur (SOA) sind die methodischen und technischen Voraussetzungen, um Geschäftsprozesse zu industrialisieren und agil zu sein. BPM schafft die Automatisierung und Standardisierung von Geschäftsprozessen, BRM die Standardisierung und Transparenz von Management-Politiken und -Prinzipien. Und eine SOA bringt die Service-Orientierung, die uns erlaubt zwischen spezifischen Logiken einzelner Prozesse und prozessübergreifenden Logiken gebündelter Kompetenzen und Dienstleistungen sauber zu trennen. Das schafft Agilität zusammen mit Industrialisierung.
Business intelligence has “invaded” the operational space in a big way, offering in-line analytics, real-time or near real-time decision-making support for all employees in the enterprise.
A key component of a company's IT framework is a business intelligence (BI) system. Traditional BI systems were designed for senior management and business analysts to report on, analyze and optimize business operations to reduce costs and increase revenues. Organizations use BI for strategic and tactical decision making where the decision-making cycle may span a time period of several weeks or months. Competitive pressures coming from a very dynamic business environment are forcing companies to react faster to changing business conditions and customer requirements. As a result, there is now a need to use BI to help drive and optimize business operations on a daily basis, and, in some cases, even for intraday decision making. This type of BI is called operational business intelligence and real-time business intelligence and it is used not only by senior management and analysts (as in traditional BI) but also by line of business managers and operational users. In other words this is BI for everyone.
This article discusses why business intelligence is often too closely associated with data warehousing and should be replaced by a concept such as decision intelligence, which could be considered a modern version of earlier decision support systems.
Embedded operational analytics help applications and business users take close to real-time action. However, there is another class of applications where even close to real-time analytics are not
sufficient.
M. Golfarelli, S. Rizzi, and I. Cella. DOLAP '04: Proceedings of the 7th ACM international workshop on Data warehousing and OLAP, page 1--6. New York, NY, USA, ACM Press, (2004)
O. Marjanovic. HICSS '07: Proceedings of the 40th Annual Hawaii International Conference on System Sciences, page 215c. Washington, DC, USA, IEEE Computer Society, (2007)