The role played by DSS in the process of decision making
The changes coming in scenario about the role of DSS in decision making.

DSS is a system that supports technological and managerial decision making by assisting in the organization of knowledge about structured, semi structured, or unstructured issues.

Decision Support Systems (DSS) are a class of computerized information system that supports decision-making activities. DSS are interactive computer-based systems and subsystems intended to help decision makers use communications technologies, data, documents, knowledge and/or models to complete decision process tasks.

Decision Support Systems have evolved over the last 25 years from inflexible mainframe systems, to isolated PC tools, to client/server data dippers, and now to high-performance and extensible enterprise decision-support applications, often involving the organization’s intranet. At the same time, the relationship between the IT Department and users has evolved from stormy to co-operative.

The huge umbrella of decision support systems (DSS) has long provided a welcome gathering spot for those interested in building software applications based on a mixture of models, data analysis, and powerful interfaces. DSS attracts practitioners, scholars and students from a range of fields including information systems, operations research/management science, computer science, psychology and other business disciplines.

The problem: There has been a virtual revolution in terms of spreadsheet based management science and operations management courses that seems to have stuck in business schools. Spreadsheets have evolved into a quite capable platform for end-user decision support modeling.

For example, within Microsoft Excel, this evolution has resulted in the inclusion of Solver for optimization, Pivot Tables, database connectivity, numerous mathematical and statistical functions and the Visual Basic for Applications (VBA) programming language.

The problem is coming from this picture where instead of using management skills for making decision, managers are very much dependent on DSS tools for making decisions. It might be more crucial when new managers will have lack of management skills and they will totally dependent on DSS tools.

So, we can make questions:

What are the reasons behind that managers are depending so much on DSS tools?
What should be the optimized ratio of using desktops and management skills for decision making?

My Idea: First of all we have to understand decision making model: the set of activities that DSS environments support. The key elements of this model are fairly common, and include:

A decision-maker: an individual or group charged with making a particular decision.
A set of inputs to the decision-making process: data, numerical or qualitative models for interpreting that data, historical experience with similar data sets or similar decision-making situations, and various kinds of cultural and psychological norms and constraints associated with decision-making
The decision-making process itself: a set of steps, more or less well-understood, for transforming the inputs into outputs in the form of decisions,
A set of outputs from the decision-making process, including the decisions themselves and (ideally) a set of criteria for evaluating decisions produced by the process against the set of needs, problems or objectives that occasioned the decision-making activity in the first place.
As soon as we look at this model, we realize that talking about decision support systems outside of a particular domain of decision-making is not particularly useful.

If we considered only the timeframe in which a given decision has to be made and the risks and constraints associated with the decision-making process, we would recognize that there is a great deal of qualitative and quantitative difference between governmental agencies, not-for-profit (NFP) organizations, and commercial firms. Put simply, commercial decisions, in the aggregate, have the shorter timeframes and higher associated risks (including extinction) than either public sector or not-for-profit decisions, and as such would presumably require the most assistance from information technology.

For this reason alone, this essay limits its scope to commercial decision support systems: IT infrastructure designed to support the decision-making processes in publicly-held and private firms that compete in open markets for customers, revenue and market share.

How do DSS environments support decision-making? DSS environments support the generic decision-making model above in a number of ways:

In decision preparation, DSS environments provide data required as input to the decision-making process. This is all about data mart and data warehousing environments do today.
In decision structuring, DSS environments provide tools and models for arranging the inputs in ways that make sense to frame the decision. These tools and models are not pivot tables and other aspects of data presentation found in query tools. They are actual decision making tools, like fault tree analysis, Bayesian logic and model-based decision-making based on things like neural networks.
In context development, DSS environments again provide tools, and provide the mechanisms for capturing information about a decision’s constituencies (who’s affected by this decision), outcomes and their probabilities, and other elements of the larger decision making context.
In decision-making, DSS environments may automate all or part of the decision-making process and offer evaluations on the optimal decision. Expert systems and artificial intelligence environments purport to do this, but they work only in very limited cases.
In decision propagation, DSS environments take the information gathered about constituencies and dependencies and outcomes and drive elements of the decision into those constituencies for action.
In decision management, DSS environments inspect outcomes days, weeks and months after decisions to see if (a) the decision was implemented/propagated and (b) if the effects of the decision are as expected.

What is required is to-

Pick the class of decision-making processes to focus on,
Narrow the range of inputs, the range of activities and the differences in models and methods,
Most importantly, to understand where technology ceases to play any meaningful role in decision-making, and where policy becomes the determinant of the quality and quantity of decisional effectiveness.

Related work:In the same context, we should understand the components of Decision support systems (DSS).Components of DSS The primary components of a DSS are a database management system (DBMS), the User Interface (Dialog) Subsystem, the Knowledge Based (Management) Subsystem.

Database management system (DBMS):- An appropriate database management system must be able to work with both data that are internal to the organization and data that are external to it.

Database
Database management system
Data directory ( A database must contain data about the tables & all other objects)
Query facility

The User Interface (Dialog) Subsystem: – Dialog generation and management system is designed to satisfy knowledge representation, and control and interface requirements.

Typical information that a decision support application might gather and present would be:

Accessing all of your current information assets, including legacy and relational data sources, cubes, data warehouses, and data marts.
The consequences of different decision alternatives, given past experience in a context that is described.
Projected revenue figures based on new product sales assumptions.

The Knowledge Based (Management) Subsystem – A knowledge based system, is a computer program that contains some of the subject-specific knowledge of one or more human experts. The most common form of expert systems is a program made up of a set of rules that analyze information (usually supplied by the user of the system) about a specific class of problems. A related term is wizard. A wizard is an interactive computer program that helps a user solves a problem. Knowledge based systems are expert in specific “application domain”.

WHAT IS ENTERPRISE CONTENT MANAGEMENT?

Enterprise Content Management (ECM) is a set of strategies, methods, and tools to capture, manage, store, preserve and deliver content and documents to enable an organization’s business processes [1]. It entails managing a document or electronic file through its life cycle from “cradle to grave.” ECM deals with content flow, the systems and processes the content touches. ECM creates value by linking people, processes and content.

ECM helps to manage unstructured data to deliver the right information to the right people, at the right level of detail, in a timely manner. It helps organizations to manage all types of electronic content, promotes collaboration and enforces consistent business processes.

Structured and Unstructured Data

Structured data is highly ordered and has attributes that let you query its database to retrieve the desired information. Enterprise Resource Planning (ERP) software for accounting, supply chain, human resources, maintenance work orders, and environment, health & safety (EHS) uses relational databases. ERP software, as well as home-grown Access databases, manages structured data with fields, columns, tables, rows and indexes.

Unstructured data lies outside of databases and is in no particular order. The vast majority of enterprise information is unstructured, and most exists as free-form text in documents, spreadsheets, e-mails, Web pages (HTML and XML), and rich media (video, audio, and image files).

ECM Features and Benefits

Enterprise Content Management extends beyond document management, with the following key features:

Document capture-capture and image paper documents, as well as native electronic files
Document management-document search, check-in, check-out, version control, access control (security), delivery
Digital asset management-maintain rich media files (audio, video, images
Business Process Management/Workflow-tools to move content through the organization, i.e., routing, approval, task management, audit trails
Collaboration-team-based content creation and decision making, i.e., document sharing, project team support, discussion boards
Web content management-create, review, publish, manage Web content from an information repository
E-mail management-classify, store, destroy per standards
Records retention and archiving-automated disposition per regulatory requirements and company policy
Content reporting-reports and statistics on the content itself.

ECM’s chief benefits are that it:

1. Provides a complete user experience;
2. Empowers people and decision making;
3. Helps to control risk and cost; and
4. Fosters agility and innovation.

ECM DRIVERS

A number of business and information technology (IT) trends drive companies to adopt ECM systems.

Business Drivers

Governance, Risk and Compliance. Compliance and records retention per EHS, HIPPA, FDA, Sarbanes-Oxley and other programs has the attention of Board and C-level executives.

Transparency. The need for accurate, transparent information, a “single version of the truth.”

Accountability. Driving accountability for day-to-day business processes to the right level within the organization.

e-Discovery. Litigation risk and electronic discovery concerns.

Productivity. The need to increase productivity and efficiency as the quantity of data continues to grow.

Collaboration. Connecting workers to relevant content and to each other, beyond e-mail and instant messaging.

Cost. Cost savings in challenging economic times.

Continuity. Capturing enterprise knowledge considering lean staffing and an aging workforce.

Information Technology Drivers

Infrastructure. Recognition of enterprise content as part of the IT infrastructure in more and more organizations.

Integration. Integrating unstructured content with Enterprise Resource Planning (ERP) databases.

Business Intelligence. Linking data from disparate sources in data warehouses or data marts.

Dashboards. Graphical display of Key Performance Indicators and scorecards using information drawn from data marts.

Web 2.0. Collaboration and social networking via the Internet.

The Cloud. Software as a Service with anytime, anywhere content delivery via Web browser over public, private, or hybrid clouds.

Security. Information security and cyber-threats.

ECM SOFTWARE OPTIONS

The market offers ECM software for businesses of all sizes. This software has capabilities well beyond shared directories on a file server and can integrate with ERP software.

Top IT infrastructure vendors EMC, IBM and Oracle lead the high-end ECM solutions market. Specialty ECM vendor Open Text Corporation offers a series of mid- to high-end LiveLink software solutions that integrate with SAP, Oracle, Microsoft, and other enterprise applications. Oracle also offers small-to mid-sized solutions. Microsoft leads the low-end ECM market with SharePoint 2010. SharePoint adoption has increased rapidly within the last few years, as a robust option for organizations that do not require dedicated ECM systems. Further, SharePoint can serve as a portal for a dedicated ECM system. SAP, HP, Xerox and others are niche ECM players [3].

TAKE ADVANTAGE OF UNTAPPED INFORMATION

Organizations overlook a large, untapped resource. By defining an ECM strategy and adopting ECM processes–typically augmented by enterprise-wide software–businesses can take advantage of this vast resource to get the right information to the right people, at the right time, in a secure manner. A variety of commercial ECM software solutions is available to fit the needs of small, medium and large organizations.

Over years BI (Business Intelligence) service providers have spent time and money to deliver best solutions to the users. Though the growth has been stagnant for a long time but now it has shown a momentum because of a rapid growth in technology and revolution in mobile based applications. The face of BI in mobile apps will change more when it will move from a dashboard providing application to a more sophisticated task specific feature. With improvement in the ability of smart phones the users not only enjoy interacting with mobile devices but also access useful information and sophisticated analysis.

BI in simple terms means technology, application or software that is used to extract, store, analyze data so as to help the management make better decisions, and BI through phones is sending business information through mobile.

It is helpful to business in several ways like:

1) Improving employee productivity – Today information system is used in CRM (Customer Relationship Management) marketing that will automate sales force management system, which involves huge cost and too much time on data entry. With implementation of these services in mobile BI, the users will get a structured management information system at less cost. This will provide accurate data for sales team as to where they are and what they want to achieve. BI applications also help sales team to represent how the services of the company can be useful to achieve targets. Moreover, it will be useful in supply chain management to form a distribution strategy for retailers and manufacturers. Several models can be proposed through mobile BI for product lifecycle management and information technology chain operations.

2) Faster decision-making – In current business scenario all the firms need information in a speedy manner so as to take accurate decisions and grab the right opportunity. The slow and inflexible business information may lead to major problems. For example, if a decline in sales has occurred in a particular region, the management cannot address the problem quickly without channelized information system. The accurate and fast information through mobile will be helpful in determining the actual cause of the problem along with quick decisions from the management front. The aim of mobile BI is not restricted to provide quality information but to enable faster decision making. Decision makers will be benefitted as it will reduce cost and increase profits by providing the historical trends and predict future estimates.

3) User friendly interface – The introduction of user friendly functions will definitely improve ROI (Return on Investment) in business. The decision makers can keep themselves updated with new trends and developments by subscribing for reports and alerts. These reports can be saved in certain formats and the mobile apps feature makes it easy to update the information from time to time. The information can be filtered by sort functions which save time. Moreover, the user can easily analyze different trends by changing the metrics or can breakdown the single report into different graphs and conduct a drill down research on the data.

There is no disputing the fact that to make decisions, you need information. Without information, you are guessing in a vacuum. If you guess instead of decide, you are reducing your chances of success with your business.

Company Decision Making

A large company will probably have, or at least should have, quite sophisticated management information systems. The systems will be computerized, bringing information from all the key areas of the business. The management team will have a process for reviewing and monitoring that information, through the circulation of summary reports, meetings (regular and ad hoc), and other means of communication.

Those same sources of management information will be used as a basis for important decision making. Past sales reports; cost reports for different products, manufacturing processes, and cost centres; market intelligence; material cost reports; supplier reliability reports. Depending on what type of decision is being made, some or all of these, plus more, may be taken into account.

There is no doubt that such information should be crucial to making key decisions in that business. However, some companies fall into the trap of allowing the information system to become an internal industry in itself, with no checks and balances. If a company becomes complacent, if the whole process becomes routine and habitual, then the value of those systems dissipates. It turns the information systems themselves into a bottomless pit for management time, bringing no valuable return.

Let me illustrate. In the early 1990′s, there was an internationally known British company, which, like most companies, had a budget setting process each year. That was an important time for decisions; absolutely critical in one of the most competitive markets in the world. That particular company was near the top of the tree, if not at the top. It had won a reputation for modernization, innovation, and efficiency, in an industry bogged down by state intervention across the world.

The whole budget setting process went on for many months before the start of the financial year. Every manager of every department was geared up for it, and it had become a highlight of management activity. So how did they go about deciding the next year’s budget for each department?

Across the board, in each department, their starting point was the current year’s budget. Each manager would add a bit here and there for anything new they needed to spend money on. We’re talking many millions of pounds here. Then the Finance Director and Chief Executive, as they went through their budget setting meetings, would get individual managers to knock off a bit to make the cost base look better. So, they would end up with a budget very much like the last, regardless of whether the last budget was nonsense.

One year the Chief Executive decided the whole system was flawed. He threw out the system of “top down” budgeting, and forced every department to start from zero. They now had to justify every penny they spent to get their budget for the year. Out went the complacency and blind acceptance of what had been happening in the past. From then on, the management were forced to justify what they were going to spend. Each item of expenditure became a decision, rather than a habit. Habits continue unless you “decide” to stop them. Fewer habits and better decisions ultimately means higher profitability.

Now, let us talk about Management Information System in detail. You must pay proper attention towards the below mentioned points.

Management Information System
Management Information System is a service that can be regarded as an amalgamation of computers, people and processes for organizing and collecting information to assist decision making. Proper information is required for taking effective decisions.

Types of MIS
Basically, there are 4 types of MIS services. They are as follows:

Transaction processing systems
Transaction processing systems basically process a huge volume of recurring and routine transactions.

Operations information systems
These kinds of systems collect inclusive information, systematize it and summarize it in a shape that is helpful for all the managers. For instance: an inventory management system.

Decision support systems
These types of systems guide managers with the essential data to make clever decisions. Basically, they have 3 basic components: record of appropriate information, administrative models and a consumer friendly interface.

Expert systems
Expert systems are basically meant to impersonate humans in taking decisions in a particular field.

Considerations
The need of human judgment is immense in today’s era as the management information systems have become more and more complex. Handling MIS services is never easy. You really need to work hard and move further in the right direction.

Developing MIS services is never easy. You really need to follow the right steps in this regard. Management Information System recognizes strategic operational and personnel and monetary shortfalls and accomplishments. An effective MIS service collects useful data in a specified time period so that it delivers the best possible results. So, these are some of the most essential points to remember regarding management information system services offered nowadays. Read this article carefully for further information. It could be of great help and guidance to you. Have a lot of fun and enjoy yourself while working on this impeccable system.

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We have marketing systems, planning systems and IT systems, yet few companies have formal ‘decision systems’. Sure we have sign off processes – but these are unstructured in terms of making a logic based decision. Thus, in absence of any formal decision system, we rely on experience, intuition and some form of collaborative communication to aggregate the ‘opinions’ of various stakeholders. Does this result in a ‘rational’ decision? In 99.99% of cases it does not. Knowledge, experience, gut feel and emotion do not constitute a ‘rational’ decision platform. Rational decision-making requires visibility of all relevant information, and resolution of various objectives, historical experiences, expectations, preferences, alternatives, probability and decision making styles.

The results of a survey analyzing the current status of corporate decision-making found that more than nine out of 10 corporate executives admit they are making important decisions on the basis of inadequate information. More than half of these senior executives are concerned that they may be making poor decisions as a result of missing information. And a quarter believes that management frequently or always gets its decisions wrong.

These poor business decisions can cost an organization millions of dollars. The main findings demonstrated few executives received the information they need, and most believed that management decision-making was only moderately effective, or worse. If these findings are not significant enough, the bigger concern is that in spite of such decision performance, only 29% of executives believed that poor decision-making structures were a common cause of bad decisions, despite 80% of respondents indicating that data is the most important factor in making decisions. On an encouraging note, respondents did rank data-based decisions higher than the opinion of others, personal intuition, or external consultancy.

The report concluded that decision making was at the core of both strategy and operations, with a vast array of factors used to balance risk and reward. Yet decision-making was not being recognized as a strategic asset.

At a time when the economy and intense global competitive pressure is driving businesses to optimize every advantage, it is clear from this study that key decision makers are not getting the data they value and need, and are relying more on “gut instinct” than proven drivers. Obviously, supporting good decisions requires a lot more than technology. It requires an Organizational culture based on logic, rather than emotion. A culture based upon:

High-quality data – the more acceptable the data, the more time spent on decision making instead of debating whether the data is correct.
Access to advanced systems and training – high quality systems require data source integration, master data management and easy user access to timely delivery of information in formats that support rapid assimilation and action.
Sound management – including governance, compliance and risk management
Trust – in both the data and the interpretation of data by others
Flexibility – to adapt actions to new insights

In 1958 a researcher from IBM introduced the term Business Intelligence along with its interpretation as “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.”

Business intelligence (more commonly referred as BI) refers to an application or a set of applications implemented by skills and technologies to help an organization to get better insight of commercial context. It may also refer to the collected set of information inclusive of statistical data.

Warehouses and Data mart are often used for data gathering by BI applications. It is not all the time that all BI Applications require a data warehouse.

How Business Intelligence is so useful?

BI technologies in combination of software application provide an organization a predictive layout of whole day to day functioning. It also provides current, legend and business operation information to the management.

Most common functional area of business support system :

Reporting
OLAP
Analysis
Benchmarking
Text mining
Data mining
Business performance management
Predictive analysis

Also, as a part of technicality, some large scale industries use their own platform to create the application which small and medium scale organization use .net framework library to create such applications.

Many changes has recently been done in form of architecture used for such applications. Now a days in 2.0 version of application SOA service oriented architecture, which enables for a flexible, composable and adaptive middleware.

The most common concepts of an information system are those in which:

o Computer networks are systems of components of information processing;

o The use of computer networks by firms are, in fact, interconnected information systems;

o Developing ways of using computer networks in business includes the design of the basic components of information systems;

o The administration of information technology emphasizes the quality and value for business and security of information systems in an organization.

The IS contains information about people, places, and those facts that help managers to make decisions, analyze and visualize complex issues and solve other problems.

For this, use a cycle of three basic activities: input, processing and output. The IS has three basic functions in the organization of a company, which has the capacity to transform information into knowledge.

o Troubleshooting, by equating the proposal of solutions to support the manager of the company to act ;

o Production of Knowledge, by obtaining information that would be difficult to access by other procedures;

o Providing an awareness in problems of organization and development.

There are some definitions of “management information system:

o System of people, equipment, procedures, documents and communications that collects, validates, processes transactions, processes, stores, retrieves and presents data for use in planning, budgeting, accounting, control and management processes for various other administrative purposes.

o Systems for processing information to become management decisions;

o Organized method of providing information from past, present and future, related to internal operations and external intelligence service. Serves to support the functions of planning, control and operation of an enterprise through the provision of information in the pattern of time appropriate to assist the decision-maker;

o Man-machine integrated system that provides information to support the functions of operation, administration and decision making in the company;

o Group of people or a set of manuals and equipment, data processing aimed to the selection, storage, processing and retrieval of data in order to reduce uncertainty in decision making through the provision of in time information for executives so they can use it for the most efficient way;

o System toward the collection, storage, retrieval and processing of information, used or desired by one or more executives to perform in its activities;

o Organized method for providing the executive of information from the past, present and future on the internal operation of the company and the business environment

o Combination of people, facilities, technology, business environment, procedures and controls, essential to process certain transactions in typical routines, to warn the executives to the significance of internal and external events, providing a basis for intelligent decision making.

Types of Information Systems

An information system should provide quality information to business and filter them by levels of decision, or subdivide them into levels, according to the hierarchical functional levels that will use them and levels of decision that should receive the information with a summary for strategic decisions.

An information system expresses a fundamental conceptual structure, depends on human resources (the end users and experts in SI), hardware (machines and average), software ( programs and procedures), data (databases and knowledge bases) and network (mean of communication and support network) to perform activities of entry, processing, production, storage and control of resources that convert data into information products.

An information system is an integral part of an organization and is a product of three components: technology, organizations and individuals, where:

o Organizations – An organization is hierarchical and structured formed. Each organization has a specific culture, or fundamental assumptions, values and methods. An organizations need to build systems to solve problems created by internal and external factors;

o People – people use information from systems based on computers in their work. They are required to enter data into the system, so that the computer can read them.

o Technology – the technology is the means by which data is processed and organized for use by people. Computers replaced the manual processing technology and can perform millions and even hundreds of millions of instructions per second. An information system has features of Information Systems. In the basic model of IS have been 5 resources keys: people, hardware, software, data and networks.

o Human resources – people are required for all information systems, which are the end users and experts in IS.

o Hardware Resources – all physical devices in equipment used in processing information.

o Software Resources-all sets of operational instructions called programs, functioning for directing and controlling the hardware, beyond the sets of instructions for processing the information.

o Resource Data – more than the raw material is in fact a valuable organizational resource to be managed effectively to benefit all end users of an organization.

o Resource Network – telecommunications networks such as the Internet, intranets and extranets, which are essential to the success in the operation of all businesses, is an important activity to characterize the success of the system.

Business Performance Management (BPM) establishes a framework to improve business performance by measuring key business characteristics which can be used to feedback into the decision process and guide operations in an attempt to improve strategic organisational performance. Other popular terms for this include; Enterprise PM (EPM), Corporate PM (CPM) Enterprise Information Systems (EIS), Decision Support Systems (DSS), Management Information Systems (MIS).

BPM: Cycle of setting objectives, monitoring performance and feeding back to new objectives.
Business Intelligence (BI) can be defined as the set of tools which allows end-users easy access to relevant information and the facility to analyse this to aid decision making. More widely the ‘intelligence’ is the insight which is derived from this analysis (eg. trends and correlations).

BI: Tools to Access & Analyse Data

Key Performance Indicators (KPIs) are strategically aligned corporate measures that are used to monitor, predict and anticipate the performance of the organisation. They form the basis of any the BPM solution and in an ideal world it should be possible to relate strategic KPIs to actual operational performance within the BI application.
KPIs provide a quick indication on the health of the organisation and guide management to the operational areas affecting performance.

In many companies analysis of data is complicated by the fact that data is fragmented within the business. This causes problems of duplication, inconsistent definitions, inconsistency, inaccuracy and wasted effort.
Silos of Data: Fragmented, Departmental Data Stores, often aligned with specific business areas.
Data Warehousing (DWH) is often the first step towards BI. A Data Warehouse is a centralised pool of data structured to facilitate access and analysis.

DWH: Centralised/Consolidated Data Store

The DWH will be populated from various sources (heterogeneous) using an ETL (Extract, Transform & Load) or data integration tool. This update may be done in regular periodic batches, as a one off load or even synchronised with the source data (real time).

ETL: The process of extracting data from a source system, transforming (or validating) it and loading it into a structured database.

A reporting (or BI) layer can then be used to analyse the consolidated data and create dashboards and user defined reports. A modelling layer can be used to integrate budgets and forecasting.

As these solutions get more complex, the definitions of the systems and what they are doing becomes more important. This is known as metadata and represents the data defining the actual data and its manipulation. Each part of the system has its own metadata defining what it is doing. Good management & use of metadata reduces development time, makes ongoing maintenance simpler and provides users with information about the source of the data, increasing their trust and understanding of it.

Metadata: Data about data, describing how and where it is being used, where it came from and what changes have been made to it.

Commercial Justifications

There is clear commercial justification to improve the quality of information used for decision making. A survey conducted by IDC found that the mean payback of BI implementation was 1.6 years and that 54% of businesses had a 5 year ROI of >101% and 20% had ROI > 1000%.

ROI on BI > 1000% from 20% of organisations

There are now also regulatory requirements to be considered. Sarbanes-Oxley requires that US listed companies disclose and monitor key risks and relevant performance indicators – both financial and non financial in their annual reports. A robust reporting infrastructure is essential for achieving this.

SarbOx requires disclosure of financial & non-financial KPIs

Poor data quality is a common barrier to accurate reporting and informed decision making. A good data quality strategy, encompassing non system issues such as user training and procedures can have a large impact. Consolidating data into a DWH can help ensure consistency and correct poor data, but it also provides an accurate measure of data quality allowing it to be managed more pro-actively.

Data Quality is vital and a formal data quality strategy is essential to continually manage and improve it.

Recent research (PMP Research) asked a broad cross section of organisations their opinion of their data quality before and after a DWH implementation.

- “Don’t know” responses decreased from 17% to 7%
- “Bad” or “Very Bad” decreased from 40% to 9%
- Satisfactory (or better) increased from 43% to 84%

DWH implementations improve Data Quality.

Tools Market Overview

At present BI is seen as a significant IT growth area and as such everyone is trying to get onto the BI bandwagon:

ERP tools have BI solutions e.g SAP BW, Oracle Apps
CRM tools are doing it: Siebel Analytics,
ETL vendors are adding BI capabilities: Informatica
BI vendors are adding ETL tools: Business Objects (BO) Data Integrator (DI), Cognos Decision Stream
Database vendors are extending their BI & ETL tools:
Oracle: Oracle Warehouse Builder, EPM
Microsoft: SQL 2005, Integration Services, Reporting Services, Analytical Services

Improved Tools

Like all maturing markets, consolidation has taken place whereby fewer suppliers now cover more functionality. This is good for customers as more standardisation, better use of metadata and improved functionality is now easily available. BI tools today can now satisfy the most demanding customer’s requirements for information.

Thinking and tools have moved on – we can now build rapid, business focussed solutions in small chunks – allowing business to see data, store knowledge, learn capabilities of new tools and refine their requirements during the project! Gone are the days of the massive data warehousing project, which was obsolete before it was completed.
A typical DWH project should provide usable results within 3 – 6 Months.

Advice & Best Practice

Initial Phase

Successful BI projects will never finish. It should perpetually evolve to meet the changing needs of the business. So first ‘wins’ need to come quickly and tools and techniques need to be flexible, quick to develop and quick to deploy.

Experience is Essential

Often we have been brought in to correct failed projects and it is frightening how many basic mistakes are made through inexperience. A data warehouse is fundamentally different to your operational systems and getting the initial design and infrastructure correct is crucial to satisfying business demands.

Keep Internal Control

We believe that BI is too close to the business and changes too fast to outsource. Expertise is required in the initial stages, to ensure that a solid infrastructure is in place (and use of the best tools and methods.) If sufficient experience is not available internally external resource can be useful in the initial stages but this MUST include skills transfer to internal resources. The DWH can then grow and evolve (with internal resourcing) to meet the changing needs of the business.

Ensure Management and User Buy In

It may sound obvious but internal knowledge and support is essential for the success of a DWH, yet ‘Reporting’ is often given a low priority and can easily be neglected unless it is supported at a senior business level. It is common to find that there is a limited knowledge of user requirements. It is also true that requirements will change over time both in response to changing business needs and to the findings/outcomes of the DWH implementation and use of new tools.

Strong Project Management

The complex and iterative nature of a data warehouse project requires strong project management. The relatively un-quantifiable risk around data quality needs managing along with changing user requirements. Plan for change and allow extra budget for the unexpected. Using rapid application development techniques (RAD) mitigates some of the risks by exposing them early in the project with the use of proto-types.

Educating the End Users

Do not under estimate the importance of training when implementing a new BI/ DWH solution. Trained users are 60% more successful in realising the benefits of BI than untrained users. But this training needs to consider specific data analysis techniques as well as how to use the BI tools. In the words of Gartner, “it is more critical to train users on how to analyse the data.” Gartner goes on to say “… that focusing only on BI tool training can triple the workload of the IT help desk and result in user disillusionment. A user who is trained on the BI tool but does not know how to use it in the context of his or her BI/DWH environment will not be able to get the analytical results he or she needs…”. Hence bespoke user training on your BI system and data is essential.

Careful planning of the training needs and making the best use of the different training mediums now available can overcome this issue. Look for training options such as: Structured classroom (on or off site), web based e-learning (CBT), on the job training & skills transfer, bespoke training around your solution & data.

Technical Overview

Information Portal: This allows users to manage & access reports and other information via a corporate web portal. As users create & demand more reports the ability to easily find, manage & distribute them is becoming more important.
Collaboration: The ability for the Information Portal to support communication between relevant people centred around the information in the portal. This could be discussion threads attached to reports or workflow around strategic goal performance.
Guided Analysis: The system guides users where to look next during data analysis. Taking knowledge from people’s heads and placing it in the BI system.
Security: Access to system functionality and data (both rows and columns) can be controlled down to user level and based on your network logon.
Dashboards & Scorecards:
Providing management with a high level, graphical view of their business performance (KPIs) with easy drill down to the underlying operational detail.
Ad-hoc Reporting and Data Analysis: End users can easily extract data, analyse it (slice, dice & drill) and formally present it in reports & distribute them.
Formatted/ Standard Reports: Pre-defined, pixel perfect, often complex reports created by IT. The power of end user reporting tools and data warehousing is now making this type of report writing less technical and more business focussed.
Tight MS Office integration: More users depend on MS Office software, therefore the BI tool needs to seamlessly link into these tools.
Write Back: The BI portal should provide access to write back to the database to maintain: reference data, targets, forecasts, workflow.
Business Modelling/ Alerting: around centrally maintained data with pre-defined, end user maintained, business rules.
Real Time: As the source data changes it is instantly passed through to the user. Often via message queues.
Near Real Time: Source data changes are batched up and sent through on a short time period, say every few minutes – this requires special ETL techniques.
Batch Processing: Source Data is captured in bulk, say overnight, whilst the BI system is offline.

Relational Database Vs OLAP (cubes, slice & dice, pivot)

This is a complex argument, but put simply most things performed in an OLAP cube can be achieved in the relational world but may be slower both to execute and develop. As a rule of thumb, if you already work in a relational database environment, OLAP should only be necessary where analysis performance is an issue or you require specialist functionality, such as budgeting, forecasting or ‘what if’ modelling. The leading BI tools seamlessly provide access to data in either relational or OLAP form, making this primarily a technology decision rather than a business one.

Top Down or Bottom Up Approach?

The top down approach focuses on strategic goals and the business processes and organisational structure to support them. This may produce the ideal company processes but existing systems are unlikely to support them or provide the data necessary to measure them. This can lead to a strategy that is never adopted because there is no physical delivery and strategic goals cannot be measured.

The bottom up approach takes the existing systems and data and presents it to the business for them to measure & analyse. This may not produce the best strategic information due to the limited data available and data quality.

We recommend a compromise of both approaches: Build the pragmatic bottom up solution as a means to get accurate measures of the business and a better understanding of current processes, whilst performing a top down analysis to understand what the business needs strategically. The gap analysis of what can be achieved today and what is desired strategically will then provide the future direction for the solution and if the solution has been designed with change in mind, this should be relatively straight forward, building upon the system foundations already in place.

Advanced Business Intelligence

The following describes some advanced BI requirements that some organisations may want to consider: Delivering an integrated BPM solution which has business rules and workflow built in allowing the system to quickly guide the decision maker to the relevant information.

Collaboration and Guided Analysis to help manage the action required as a result of the information obtained.
More user friendly Data Mining and Predictive Analytics, where the system finds correlations between un-related data sets in order to find the ‘golden nugget’ of information.

More integration of BI information into the Front Office Systems e.g. a gold rated customer gets VIP treatment when they call in, data profiling to suggest this customer may churn, hence offer them an incentive to stay.

Increased usage of Real Time data.

End to end Data Lineage automatically captured by the tools. Better metadata management of the systems will mean that users can easily see where the data came from and what transformations it has undergone, improving the trust in the data & reports. Systems will also be self documenting providing users with more help information and simplifying ongoing maintenance.

Integrated, real time Data Quality Management as a means to measure accuracy of operational process performance. This would provide cross system validation, and verify business process performance by monitoring data accuracy, leading to better and more dynamic process modelling, business process re-engineering and hence efficiency gains.

Packaged Analytical Applications like finance systems in the 80′s and packaged ERP (Enterprise Requirement Planning) in the 90′s. Packaged BI may become the standard for this decade. Why build your own data warehouse and suite of reports and dashboards from scratch when your business is similar to many others? Buy packaged elements and use rapid deployment templates and tools to configure them to meet your precise needs. This rapid deployment capability then supports you as your business evolves.

BI for the masses: As information becomes more critical to manage operational efficiencies, more people need access to that information. Now the BI tools can technically and cost effectively provide more people with access to information, BI for the masses is now reality and can provide significant improvement to a business. The increased presence of Microsoft in the BI space will also increase usage of BI and make it more attractive. BusinessObjects’ acquisition of Crystal and recent release of XI will also extend BI to more people, in and outside the organisation – now everyone can be given secure access to information!

Conclusion

The potential benefits from a BI/DWH implementation are huge but far too many companies fail to realise these through: lack of experience, poor design, poor selection and use of tools, poor management of data quality, poor or no project management, limited understanding of the importance of metadata, no realisation that if it is successful it will inevitably evolve and grow, limited awareness of the importance of training….. with all these areas to consider using a specialist consultancy such as IT Performs makes considerable sense.