Business intelligence

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Business intelligence (BI) has two basic different meanings related to the use of the term intelligence. The primary, less frequently, is the human intelligence capacity applied in business affairs/activities. Intelligence of business is a new field of the investigation of the application of human cognitive faculties and artificial intelligence technologies to the managerial intelligent decision support systems for different business problems, see for example BI as a cognitive capacity.

The second, which is the subject of this article, relates to the intelligence as information valued for its currency and relevance. It is expert information, knowledge and technologies efficient in the management of organizational and individual business. Therefore, in this sense, business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all of the factors that affect your business. It is imperative that you have an in depth knowledge about factors such as your customers, competitors, business partners, economic environment, and internal operations to make effective and good quality business decisions. Business intelligence enables you to make these kinds of decisions.

Business Intelligence should not be confused with competitive intelligence, which is a separate business discipline.

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[edit] Reasons for Business Intelligence

Business Intelligence enables organizations to make well informed business decisions and thus can be the source of competitive advantages. This is especially true when you are able to extrapolate information from indicators in the external environment and make accurate forecasts about future trends or economic conditions. Once business intelligence is gathered effectively and used proactively you can make decisions that benefit your organization before the competition does.

The ultimate objective of business intelligence is to improve the timeliness and quality of information. Timely and good quality information is like having a crystal ball that can give you an indication of what's the best course to take. Business intelligence reveals to you:

  • The position of your firm as in comparison to its competitors i.e. market share
  • Changes in customer behaviour and spending patterns
  • Customers' preferences
  • The capabilities of your firm
  • Market conditions, future trends, demographic and economic information
  • The social, regulatory, and political environment
  • What the other firms in the market are doing

You can then deduce from the information gathered what adjustments need to be made.

Businesses realize that in this very competitive, fast paced, and ever-changing business environment, a key competitive quality is how quickly they respond and adapt to change. Business intelligence enables them to use information gathered to quickly and constantly respond to changes.

[edit] Benefits of BI

BI provides many benefits to companies utilizing it. It can eliminate a lot of the guesswork within an organization, enhance communication among departments while coordinating activities, and enable companies to respond quickly to changes in financial conditions, customer preferences, and supply chain operations. BI improves the overall performance of the company using it.

Information is often regarded as the second most important resource a company has (a company's most valuable assets are its people). So when a company can make decisions based on timely and accurate information, the company can improve its performance. BI also expedites decision-making, as acting quickly and correctly on information before competing businesses do, which can often result in competitively superior performance. It can also improve customer experience, allowing for the timely and appropriate response to customer problems and priorities.

[edit] Factors Influencing Business Intelligence

Customers are the most critical aspect to a company's success. Without them a company cannot exist. So it is very important that you have information on their preferences. You must quickly adapt to their changing demands. Business Intelligence enables you to gather information on the trends in the marketplace and come up with innovative products or services in anticipation of customer's changing demands.

Competitors can be a huge hurdle on your way to success. Their objectives are the same as yours and that is to maximize profits and customer satisfaction. In order to be successful you must stay one step ahead of your competitors. In business you don't want to play the catch up game because you would have lost valuable market share. Business Intelligence tells you what actions your competitors are taking, so you can make better informed decisions.

Business Partners must possess the same strategic information you have so that there is no miscommunication that can lead to inefficiencies. For example it is common now for businesses to allow their suppliers to see their inventory levels, performance metrics, and other supply chain data in order to collaborate to improve supply chain management. With Business Intelligence you and your business partners can share the same information.

Economic Environment such as the state of the economy and other key economic indicators are important considerations when making business decisions. You don't want to roll out a new line of products during an economic recession. BI gives you information on the state of the economy so that you can make prudent decisions as to when is the right time to maybe expand or scale back your business operations.

Internal Operations are the day to day activities that go on in your business. You need an in depth knowledge about the internal workings of your business from top to bottom. If you make an arbitrary decision without knowing how your entire organization works it could have negative effects on your business. BI gives you information on how your entire organization works. Cost monitoring to ensure bottom line is one such internal operation where BI can add a lot of value to the organisation.


[edit] BI Technology Requirements

For the BI system to work effectively, enterprises must address the following technical issues:

  • Security and specified user access to the warehouse
  • Data volume (capacity)
  • How long data will be stored (data retention)
  • Benchmark and performance targets

[edit] BI software types

People working in business intelligence have developed tools that ease the work, especially when the intelligence task involves gathering and analyzing large quantities of unstructured data. Each vendor typically defines Business Intelligence their own way, and markets tools to do BI the way that they see it.

Business intelligence includes tools in various categories, including the following. For examples of implemented Business Intelligence systems, see the BI screenshot collection at The Dashboard Spy.

[edit] History

An early reference to non-business intelligence occurs in Sun Tzu's The Art of War. Sun Tzu claims that to succeed in war, one should have full knowledge of one's own strengths and weaknesses and full knowledge of one's enemy's strengths and weaknesses. Lack of either one might result in defeat. A certain school of thought draws parallels between the challenges in business and those of war, specifically:

  • collecting data
  • discerning patterns and meaning in the data (generating information)
  • responding to the resultant information

Prior to the start of the Information Age in the late 20th century, businesses sometimes struggled to collect data from non-automated sources. Businesses then lacked the computing resources to properly analyze the data, and often made business decisions primarily on the basis of intuition.

As businesses started automating more and more systems, more and more data became available. However, collection remained a challenge due to a lack of infrastructure for data exchange or to incompatibilities between systems. Analysis of the data that was gathered and reports on the data sometimes took months to generate. Such reports allowed informed long-term strategic decision-making. However, short-term tactical decision-making continued to rely on intuition.

In modern businesses, increasing standards, automation, and technologies have led to vast amounts of data becoming available. Data warehouse technologies have set up repositories to store this data. Improved Extract, transform, load (ETL) and even recently Enterprise Application Integration tools have increased the speedy collecting of data. OLAP reporting technologies have allowed faster generation of new reports which analyze the data. Business intelligence has now become the art of sifting through large amounts of data, extracting pertinent information, and turning that information into knowledge upon which actions can be taken.

Business intelligence software incorporates the ability to mine data, analyze, and report. Some modern BI software allow users to cross-analyze and perform deep data research rapidly for better analysis of sales or performance on an individual, department, or company level. In modern applications of business intelligence software, managers are able to quickly compile reports from data for forecasting, analysis, and business decision making.

In 1989 Howard Dresner, a Research Fellow at Gartner Group popularized "BI" as an umbrella term to describe a set of concepts and methods to improve business decision-making by using fact-based support systems. Dresner left Gartner in 2005 and joined Hyperion Solutions as its Chief Strategy Officer.

[edit] The Future of Business Intelligence

In this rapidly changing world consumers are now demanding quicker more efficient service from businesses. To stay competitive, companies must meet or exceed the expectations of consumers. Companies will have to rely more heavily on their business intelligence systems to stay ahead of trends and future events. Business intelligence users are beginning to demand [Real time Business Intelligence] or near real time analysis relating to their business, particularly in frontline operations. They will come to expect up to date and fresh information in the same fashion as they monitor stock quotes online. Monthly and even weekly analysis will not suffice. "Business users don't want to wait for information. Information needs to be always on and never out of date. This is the way we live our lives today. Why should Business Intelligence be any different?" Charles Nicholls, CEO of SeeWhy, a Software company, Windsor UK.

In the not too distant future companies will become dependent on real time business information in much the same fashion as people come to expect to get information on the internet in just one or two clicks. "This instant "Internet experience" will create the new framework for business intelligence, but business processes will have to change to accommodate and exploit the real-time flows of business data." -- Nigel Stokes, CEO, DataMirror Corp., Toronto

"BI 2.0" is the recently-coined term which is part of the continually developing Business Intelligence industry and heralds the next step for BI. "BI 2.0" is used to describe the acquisition, provision and analysis of "real time" data, the implication being that earlier Business Intelligence and Data Mining products (BI 1.0?) have not been capable of providing the kind of timely, current data end-users are now clamoring to have. Realizing that hype has historically outpaced reality as Business Intelligence software companies compete for marketshare, it would be wise to keep in mind the observation of veteran analyst Andy Hayler as they now begin to describe their products in terms of the "real time" and "BI 2.0" nomenclature. Hayler recently wrote the following in an article titled, "Real Time BI - Get Real":

"I permitted myself a wry smile when I first heard the hype about 'real time' business intelligence". Hayler then goes on to explain, "The mismatch between fantasy and reality is driven by two factors. The first is that business rules and structures (general ledgers, product classification, asset hierarchies, etc.) are not in fact uniform, but are spread out among many disparate transaction system implementations...The second problem is that the landscape of business structures is itself in constant flux, as groups reorganize, subsidiaries are sold or new companies acquired".

So long as Business Intelligence relies upon some kind of data warehouse structure (including web-based virtual data "warehouses"), data will have to be converted into what Hayler calls "a lowest common denominator consistent set." When it comes to dealing with multiple, disparate data sources and the constantly changing, often volatile, business environment which requires tweaking and restructuring of IT systems, getting BI data in a genuinely true, "real time" format remains, again according to Hayler, "a pipe dream...As long as people design data models and databases the traditional way, you can forget about true 'real-time' business intelligence across an enterprise: the real world gets in the way".

So, does this mean that "BI 2.0" is unattainable? Notice that, in Hayler's opinion, the caveat here has to do with data models and databases. If the design continues to remain essentially the same, the possibility of "real time" Business Intelligence is remote, so far as he can determine. However, rather than focusing on databases and their resistance to having any kind of change in structure, what if there was a way to bypass the database architecture and directly capture the data? This "outside the box" approach would allow real-time access to data. This is essentially what the new MSSO Technology has done. With MSSO, "real time" BI 2.0 is now not only within reach, it has become a reality.

Also in the near future business information will become more democratized where end users from throughout the organization will be able to view information on their particular segment to see how it's performing.

So, in the future, the capability requirements of business intelligence will increase in the same way that consumer expectations increase. It is therefore imperative that companies increase at the same pace or even faster to stay competitive.

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[edit] Key Intelligence Topics

BI often uses Key performance indicators (KPIs) to assess the present state of business and to prescribe a course of action. More and more organizations have started to make more data available more promptly. In the past, data only became available after a month or two, which did not help managers to adjust activities in time to hit Wall Street targets. Recently, banks have tried to make data available at shorter intervals and have reduced delays.

The KPI methodology was further expanded with the Chief Performance Officer methodology which incorporated KPIs and root cause analysis into a single methodology.

[edit] KPI example

For example, for businesses which have higher operational/credit risk loading (for example, credit cards and "wealth management"), a large multi-national bank makes KPI-related data available weekly, and sometimes offers a daily analysis of numbers. This means data usually becomes available within 24 hours, necessitating automation and the use of IT systems.

[edit] Designing and implementing a business intelligence program

When implementing a BI programme one might like to pose a number of questions and take a number of resultant decisions, such as:

  • Goal Alignment queries: The first step determines the short and medium-term purposes of the programme. What strategic goal(s) of the organization will the programme address? What organizational mission/vision does it relate to? A crafted hypothesis needs to detail how this initiative will eventually improve results / performance (i.e. a strategy map).
  • Baseline queries: Current information-gathering competency needs assessing. Does the organization have the capability of monitoring important sources of information? What data does the organization collect and how does it store that data? What are the statistical parameters of this data, e.g. how much random variation does it contain? Does the organization measure this?
  • Cost and risk queries: The financial consequences of a new BI initiative should be estimated. It is necessary to assess the cost of the present operations and the increase in costs associated with the BI initiative? What is the risk that the initiative will fail? This risk assessment should be converted into a financial metric and included in the planning.
  • Customer and Stakeholder queries: Determine who will benefit from the initiative and who will pay. Who has a stake in the current procedure? What kinds of customers/stakeholders will benefit directly from this initiative? Who will benefit indirectly? What are the quantitative / qualitative benefits? Is the specified initiative the best way to increase satisfaction for all kinds of customers, or is there a better way? How will customers' benefits be monitored? What about employees,... shareholders,... distribution channel members?
  • Metrics-related queries: These information requirements must be operationalized into clearly defined metrics. One must decide what metrics to use for each piece of information being gathered. Are these the best metrics? How do we know that? How many metrics need to be tracked? If this is a large number (it usually is), what kind of system can be used to track them? Are the metrics standardized, so they can be benchmarked against performance in other organizations? What are the industry standard metrics available?
  • Measurement Methodology-related queries: One should establish a methodology or a procedure to determine the best (or acceptable) way of measuring the required metrics. What methods will be used, and how frequently will the organization collect data? Do industry standards exist for this? Is this the best way to do the measurements? How do we know that?
  • Results-related queries: Someone should monitor the BI programme to ensure that objectives are being met. Adjustments in the programme may be necessary. The programme should be tested for accuracy, reliability, and validity. How can one demonstrate that the BI initiative (rather than other factors) contributed to a change in results? How much of the change was probably random?.

[edit] See also

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