The BI Pentagon of Success: The Importance of Project Delivery

Gartner defines BI as an umbrella term that spans the people, processes and applications/tools to organise information. This is alongside assisting the accessing and analysing of the data, improving decisions and managing performance.

BI also covers schemes and strategies that help businesses to collect data from internal and external sources, thereby making it prepared for full spectrum analysis. BI facilitates the creation and execution of queries in order to gain valuable insight from the data, generating exceptional reports and charts for data visualisations.

Modern business intelligence frequently includes methods like data mining, quantitative analysis, statistical inferences, and a myriad of predictive data analytics. These methods are based on customers, products, services, marketing, HR, supply chain, healthcare, web, social media, sentiments and feedback, all designed for effective decision making.

BUILDING UP

Building and implementing BI systems necessitate organisations to have some background of working with raw information and information technologies. The prerequisites, in general terms, could be classified as:

1.     In-depth understanding of the present and future information necessities.

2.     Developing the culture of information and intelligence sharing.

3.     Sharing of synchronised business objectives with all the stakeholders.

Undertaking the implementation of BI systems is a first essential process needed to determine a general vision of such systems. It involves specifying the informational needs of each organisation, whilst simultaneously paying attention to key decision makers and subject matter experts. Suggestions on building a specific methodology may turn out to be a set of refined guidelines and an adaptation to patterns based on best industry practices.

PEOPLE

Universal adoption by business users represents the key for any BI design and architecture. The enterprise does not benefit if the BI mentor team provides comprehensive information that the business simply does not use. Consequently, BI planners should ideally focus most on understanding user’s roles and how BI will fit within the processes they support. The end users, or project people, can be easily categorized into three types for better BI synergies:-

(1) Originator: Individuals who define and carry out domain specific analysis on data.

(2) Consumer: Line of business users who handle BI and its analytic results for improving decisions and increasing performances. This category may comprise of people from clerical workers to senior executives.

(3)  Enabler: Typically a team of facilitators who carry out ancillary tasks (traditionally IT department) required to implement solutions. However, with the discovery of packaged applications and technologies like BI, has now given user-friendly environments (UI/UX) to the operator, helping users’ self- service with less dependence on enablers.

Most BI models pay large attention to the role of end users in the whole life cycle of BI roll out. Increasingly, a broader set of users in a variety of roles are empowered to enable, produce and consume analytic contents.

Parameterisation of the BI systems, carried out by its user, is obligatory for its efficient performance. Establishing the same system plays a significant role, involving repositories of knowledge assembled from its people and business partners (customers, suppliers, contractors, service providers). Optimal usage of BI systems is possible only when it is driven by people who are:

1.     Quick learners that interpret results and ask intelligent questions.

2.     Self-servicing, creating their own analysis and reports.

3.     Vigilant of analysis and aggressively modifying repositories.

4.     Identifying and compiling modeling knowledge.

5.      Passionate about improving the decision making processes.

PROJECT LIFE CYCLE

The creation and consumption of BI remain the two primary iterative stages in the life cycle of any BI framework. BI creation spectrum covers the definition of BI, the formulation of development strategy and the identification of tools. It helps close in on design/layout and conclusions regarding implementation approach, whilst making regular data discoveries and exploration.

At this stage, it is necessary to identify areas and business processes that will initially undertake the hammering of BI tools. Empirically it has been established that most setups, that have implemented the path, have adopted characteristics of a top-down approach, i.e. decisions taken by the board and then duly supported by the lower hierarchies of management. This enhances the significance of whether a particular BI solution is designed to be implemented in one function or to cover a selected range of business domains.

In the process of formulating potential BI systems, it is worth considering whether new systems would work in online or offline mode. Could newly designed systems be directed towards predictive exploration of structured and unstructured data, or would they only remain focused on descriptive analysis based on legacy transaction entries.

The decision at this stage originates from the potential simplicity or complexity of the BI solution. Could it develop a window for assimilating diverse business activities and functions expected to be undertaken by the enterprise.

Methodology deployment initiatives for any BI project are complex, covering multiple functions, departments and processes. It is expected to deliver accurate information to the correct user at the right time, whilst simultaneously avoiding fragmenting and tactical errors. Regardless of the methodology, a BI moderator has to employ certain basic BI iterations for a winning outcome; like the identification of business requirements, detailed data analysis and the adoption of proven architecture. A BI moderator must also investigate data integration through ETL and virtualisation, a friendly UI/UX front end development, module and composite testing and release management. If one chooses to integrate testing with development, or employ prototypes and sprints, it doesn't negate the important ingredients of the business intelligence lifecycle process; design, development and testing.

It should be emphasised that in order to deliver enhanced business value, BI processes and methodologies should integrate with the rest of the portfolios that the enterprise utilises. A lack of integration amongst major framework components could create organisational and data quality setbacks, which may compromise the value of the BI.

Maninder Singh is a leader in Cloud Business Intelligence and Analytics with more than a decade of experience. He is the author of the Flagship Model: The BI Pentagon of Success. Many thanks to Hannah Jones and Harpreet Singh for their contributions to this article.

Want to know more about the BI Pentagon of Success? Connect with our LinkedIn to ensure you have access to our forthcoming series of articles that will explore the individual sub dimensions in more depth.