The business value of Business Intelligence

In the nineties, much investment in IT was focussed on enterprise applications - such as Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Customer Relationship Management (CRM) - and on connectivity between trading partners via the internet and more traditional means such as Electronic Data Interchange (EDI). The primary motivation for many of these investments was to achieve better control over day-to-day operations. The goal of this blog is to contribute to the emerging dialogue on the subject of the business value of Business Intelligence.

These applications were considered sources of data that were used to provide Business Intelligence. In those times, we also saw the emergence and maturation of data warehousing as a specialty field focused on helping organizations make better use of the vast amounts of raw transactional data captured by enterprise applications. From the technical side, these challenges used to be called Extract Transform Load (ETL), data storage, and information delivery and were addressed by -

— Relevant products
— A growing body of data warehousing management knowledge
— The evolution of well-defined data warehousing architectures that could be applied in many organizational contexts

New beginnings

As the nineties came to a close, enterprise applications had been widely adopted by major organizations, and innovators were beginning to look at how to leverage IT for purposes such as strategic enterprise management, managing customer profitability, improving supply chain and/or operations performance, improving ‘front-office’ business processes (such as budgeting and business planning). We are now presented with an opportunity to marry organizational desire to better leverage information with the technical ability to deliver information to support a wider variety of business processes that impact the bottom line.

The vendors in the BI community have recognized this opportunity and are delivering a steady stream of innovative BI products. Another point of note is that there are existing BI tools that have yet to be as fully exploited, the results of which could be the use of optimization tools for tactical and operational process improvements to supply chain and operations. Therefore, it is a strategic necessity for organizations to assess how they can use BI to improve results and to use structure approaches to ensure that investments in BI deliver business value.

Capture business value of Business Intelligence

In economic terms, the business value of an investment (as an asset) is measured as the net present value of the after-tax cash flows associated with the investment. Likewise, the quest for delivering business value via BI can be seen as a matter of determining how an organization can use BI to:

— Improve management process - such as planning, controlling, measuring, monitoring, and/or changing so that management can increase revenues, reduce costs, or both

— Improve operational processes - such as fraud detection, sales, campaign execution, customer order processing, purchasing, and/or accounts payable processing so that the business can increase revenues, reduce costs or both

Align BI with strategy  

As data warehousing matured in the 1990s, a considerable body of expertise developed around the task of aligning the use of BI with organizational strategies. Essentially, it is a matter of these four activities.

— Understanding the strategic drivers of the competitive environment (private  industry) or organizational environment (government and non-profit) and related business goals

— Determining the business questions for which answers are required to plan, budget, control, monitor, measure, assess, and/or improve organizational performance concerning the strategic goals.

— Identifying the tools, methods, and analytical frameworks that can be used to support the execution of key business processes and management of organizational performance.

— Following well-established technical procedures for identifying, acquiring, integrating, staging, and delivering the data and information managers need

Engineer the process

Below are the processes that need to be engineered for a successful measure of ROI on Business Intelligence.

— Strategic, tactical, and operational planning processes
— Financial, operational, marketing, product development, and human resources management processes
— performance monitoring and measurement processes, quality management processes, and continuous improvement processes
— supply chain and customer relationship management processes

Business Value Analysis

We have examined strategic alignment, management process engineering, and change management as key preconditions for ensuring that BI investment results in business value. At Celeix Digital, we believe there is no shortcut to rigorous up-front business value analysis of how investments in BI will deliver business value. While traditional return on investment analysis is certainly a key component of Business Value Analysis, we recommend taking a broader analytical perspective, consisting of —

BI Opportunity Analysis — combines environmental analysis, industry analysis, and business strategy review with a comprehensive assessment of how BI can be used to enable critical strategies and support key business processes to improve revenue and reduce costs.

BI Readiness Assessment — applies readiness assessment instruments to assess organizational, business, and technical readiness to deliver information to feed BI applications and frameworks. It extends BI readiness assessments by using BI maturity assessment to evaluate organizational management and decision-making cultures, capacity for change, and change management capabilities as they affect the use of BI and structured analytical methods.

Process Engineering — determines and specifies exactly how BI applications will be used in the context of the management processes to plan, control, measure, manage, and improve the business processes of the organization that drives revenue and costs.

ROI Analysis — uses investment cost estimated and discounted cash flow analysis to estimate the net present value of after-tax cash flows that will result from the investment in a BI initiative. It also uses other conventional approaches, such as cost-benefit or payback, if required by the organizational capital budgeting process.

Change Analysis — extends the results of process engineering by assessing the degree of process change required, the degree of individual change required, the skills required by new management processes, and the training required for various types of users.

Managing for Business Value Delivery

As with any capital project, capturing the business value projected for the investment requires effective management. At Celeix Digital, we believe the more substantial challenge lies in meeting the business preconditions, particularly the need for process engineering and change management. Ultimately, capturing the business value of BI is a strategic challenge and opportunity, and we have seen that the potential for BI is substantial. With appropriate rigor and a willingness to manage for business value, there is no reason that organizations cannot capture the business value of Business Intelligence, however, that might be defined in their specific circumstances.