Business Intelligence Maturity Model

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By Shavindri Ratnayake

In today’s world Business Intelligence (BI) can be defined as the use of technologies, applications, and practices for the collection, integration, analysis, and presentation of business information. It involves the gathering and processing of data from various sources within and outside an organization to generate actionable insights that support informed decision-making. BI encompasses a wide range of activities, reporting, query and analysis, performance monitoring, and predictive analytics. The goal of BI is to help organizations gain a deeper understanding of their operations, identify trends and patterns, optimize processes, and ultimately achieve strategic objectives.

The importance of BI is further emphasized by the Business Intelligence Maturity Model. While some businesses may thrive at lower maturity levels, others need higher levels of BI maturity to succeed. In the lower levels in the maturity model, use of spreadsheets and simple reporting tools for ad hoc based analysis while in the top levels in the maturity model sophisticated data driven decision support systems are used. BI maturity models identify areas for improvement within organizations, focusing on reporting, analysis, and key success indicators, and suggest strategies for leveraging BI to create business value.

In the initial stage of business maturity, BI models are applied informally before the introduction of data warehousing, facilitating quicker access to timely information. As organizations progress to the second stage, they begin to grasp the significance of information and its relevance to their business needs, thereby recognizing the importance of BI data. Finally, in the advanced stage of business maturity, organizations fully engage in optimizing decision-making processes, managing business operations, and implementing organizational changes by leveraging the complete potential of business intelligence.

Gartner’s BI Maturity Model

Gartner’s BI maturity model is often regarded as superior to other maturity models due to several reasons. Gartner’s model provides a comprehensive framework that covers various aspects of business intelligence, including technology, processes, and people. It considers organizational maturity across multiple dimensions, offering a holistic view of BI implementation.

Gartner, as a leading research and advisory firm in the technology industry, ensures that its maturity model aligns with industry standards and best practices. This alignment enhances the model’s credibility and relevance to businesses worldwide.

The five levels of maturity, by considering, Gartner’s maturity model for business intelligence and performance management, are unaware, tactical, focused, strategic and pervasive through assessment of key areas such as people, processes and metrics and technology.

1. Unaware Stage

During the unaware stage, organizations struggle with inaccurate and inconsistent data interpretation, lacking the necessary changes to meet the information needs of individuals and departments. Spreadsheets are heavily relied upon, with minimal utilization of reporting tools or dashboards. The company lacks a standardized set of reports for informational and performance management purposes. Information management and reporting predominantly fall under the responsibility of the IT department, with minimal investment in dedicated information management initiatives.

2. Tactical Stage

In the tactical level, the organizations invest in BI and reporting, by considering department level metrics, and there is some level of off the shelf software with very few modifications, to manage company needs and users may not be skilled enough to take complete advantage of the system. There is no 100% guarantee to the management on the quality and consistency of the system, as there is low support and inadequate funding on the initial BI projects.

3. Focused Stage

In the level of ‘focused’, the organization achieves first successes and brings a certain level of benefits to the organization. A certain business unit, a department or a member of senior management is responsible for IT management and creation of management dashboards to optimize the efficiency of individual business units, the company achieve company goals sustainably by managing inconsistencies. BI projects are funded by business units within the organization and in this stage, data is not integrated, and are available through individual stovepipe solutions. Often closed software applications to capture data related to reporting which cover a certain part of the business.

4. Strategic Stage

When an organization is in the strategic stage, there is a clear business strategy to achieve business objectives through BI and reporting through top management sponsorships and critical business processes are led by business intelligence and project management. Usage of business intelligence begins from within the organization and extends to suppliers, customers and business partners with enough funding to achieve goals. There is a strategic framework during the strategic stage and to deliver financial and other strategic goals and quality of data is made sure to be trustworthy and reliable to be used for strategic decision making.

5. Pervasive Stage

Business intelligence and reporting is widely used during the Pervasive stage, and it becomes a crucial part of the business processes during this stage. BI and reporting framework is built in a way to flexibly support business processes and proactively support changes in the business world and dynamic demands of information needs. Information used for reporting and analysis is trustworthy with a high level of data quality and used effectively within each level of the company and BI uses are available for business partners, suppliers, and customers etc.

Historical progress on the adoption of Business Intelligence

Business analytics has been used for a long time in the IT industry before the popularity of advanced tools and techniques that we use currently. For instance, businesses used to use handwritten notes to report on their yearly performance. To find out what prompted customers to buy and use things again, savvy businesspeople used to investigate products using surveys and customer feedback. However, all of this required manual labour and availability. This drastically changed as technologies for complicated business analytics were gradually ingrained into our society. These were followed by subsequent generations, who permanently changed the globe. Businesses across the world have embraced the advancement of business analytics.

Business analytics is utilized everywhere to optimize a company’s operational (business) affairs, from finances and marketing to performance or operations analytics. Even in the absence of the cutting-edge tools and methods we currently have at our disposal, business analytics has been around for a very long time. For example, merchants used to rely on handwritten remarks to reflect on the annual performance of their business. When tools for complex business analytics were gradually incorporated into our culture, this was radically altered. Later generations of business analysts followed these and irrevocably altered the world. Smart businesspeople used to research items using surveys and customer feedback to determine what compelled consumers to purchase and use products repeatedly.

BI Dissemination

1. Unaware Stage

At this level, BI and analytics are ad hoc, lacking formal decision-making processes or practices. Requests for information from executives and managers prompt users to scramble for data from any available operational application. The enterprise lacks an information infrastructure, with undefined processes for analytics, decision-making, or performance metrics. This approach persists due to its low initial cost.

2. Opportunistic Stage

At this stage, business units undertake separate BI or analytics projects to enhance processes or assist in tactical decision-making. Each project operates independently with its own infrastructure, tools, and metrics, leading to a proliferation of applications across the organization. Process modelling is minimal, with reliance on data integration tools, databases, and BI platforms. Output is delivered through reports, queries, and dashboards, supported by single-subject data marts and potentially data quality technology. Packaged analytic applications often cater to specific business domains.

3. Standards Stage

At this stage of maturity, coordination among people, processes, and technologies within the enterprise begins to take shape. A senior executive, often from the business side, assumes the role of championing BI and analytics initiatives. Process managers and IT leaders oversee projects spanning various business processes, like finance or marketing, requiring shared analysis and decision-making. Users leverage multiple data streams to make decisions, weighing trade-offs. Many enterprises establish BI competency centres (BICCs) or analytics centres of excellence to foster expertise sharing and ensure consistency in specific information applications. Technology standards, though not mandated, begin to emerge, encompassing information infrastructure, data warehouses, and BI platforms for scalability and support. However, there’s limited consistency in data and analytic model sharing across projects, with only a few processes sharing common master data models.

4. Enterprise Stage

At this level, top executives become the program’s sponsors. This may be the CEO (directly) in smaller organizations, or multiple executives (including the CFO, CMO and COO) in larger organizations. The enterprise has defined a framework of performance metrics that links multiple processes to enterprise goals. These metrics guide enterprise strategy. BI applications support cross-functional or enterprise-wide decision processes. Corporate and operational executives can see cause-effect relationships among key activities. Everyone, from analysts to business managers and senior executives, uses the same BI and analytics systems. An enterprise information architecture guides the design of new systems. Enterprise information management (EIM) and information sharing mature and receive significant funding. The companies in “Enterprise stage” exhibits a high degree of discipline around BI and analytics projects. Teams pursue projects with sophisticated processes and skills for requirements’ definition, modelling and program management that includes agile development and rapid prototyping. Common data models, rules and analytics minimize the number of versions of a given set of information.

5. Transformative Stage

At this advanced stage, BI and analytics evolve into a strategic initiative, jointly managed by both business and IT sectors, and backed by top-level organizational support. The CEO may spearhead the program, or roles like Chief Analytics Officer (CAO) or Chief Data Officer (CDO) might be established. Information is perceived as a strategic asset, and BI and analytics are leveraged to drive revenue, enhance operational efficiency, or deliver exceptional customer service. The enterprise extends its performance metrics framework to include partners and customers, emphasizing business value over internal processes. Stakeholders utilize BI and analytics insights to coordinate responses to evolving business conditions throughout the value chain and make transformative decisions. Users span various organizational levels, business units, geographic locations, customers, and partners, all relying on trustworthy information and analysis to pursue strategic objectives.

BI Dissemination in stages

BI Dissemination in stages

In conclusion, accomplishing development in business intelligence is significant for organizations due to a few key reasons. Firstly, it empowers organizations to use information viably, picking up experiences that drive educated decision-making and key arranging. Furthermore, BI development cultivates operational effectiveness by optimizing forms and asset allotment based on data-driven experiences. Eventually, BI development enables organizations to remain competitive, improve, and flourish in today’s energetic trade scene, making it an imperative component of long-term victory and maintainability.

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