Here, we will discuss the importance of self service in the current business scenario and how self-service BI can help businesses leverage information to their advantage, improve agility in responding to market change and reduce cost. We will also discuss key success factors for robust implementation and a methodology for self-service BI.
How is Business Using BI Today?
Business intelligence has come a long way since its inception in 1980s. While the fundamental objective of supporting business decisions remains the same , BI is now at the juncture where business needs to perform more analysis on more data from more disparate sources in less time and for less money. Before we get into whether BI meets expectations or not, let’s see how BI is being used today from a usage standpoint. Figure 1 shows analysis from TWDI Research, which shows usage is limited in most categories, with only one-fourth of business users utilizing BI.
Let’s examine how different groups within organizations leverage BI.
End user community (including operational users, middle management and senior management): This user community essentially depends on canned reports developed by IT or power users. They may use some flexible analysis, such as drill through capabilities and report formatting. In any organization this is a large user base, yet they are not leveraging BI capabilities effectively.
Power user community/Analysts: The power users including analysts, in a given function or business unit are more BI literate and are able to generate reports leveraging IT-enabled content/data. The extent of usage varies greatly in organizations depending on toolsets used, available training and skill levels and processes used.
It must be also noted that significant analysis still continues with spreadsheets. While this potentially satisfies an immediate need, it indicates that either BI tools are not able to provide the required functionality or users are not trained to leverage investments in BI. There are many ad hoc analytics requirements which are never fulfilled; if it takes too much time to get answers, then the questions become irrelevant.. Thus, there are unfulfilled requirements that BI is not able to address.
While BI has evolved and matured, there are still battles to be won. Before we look at how self-service BI can help, let’s see what business expects from BI.
What Does Business Expect from BI Today?
The biggest concerns about BI are whether it lives up to its expectations and whether users get their money’s worth from their investment. While there is no easy or single answer to these issues, there are few areas where BI has underdelivered.
- Penetration of BI remains low in most organizations, possibly because BI has not met expectations from all quarters.
- Due to increased centralization, BI has not adapted to change or responded to business demands quickly.
As companies are fiercely competing in the marketplace, the business model is constantly evolving. This means BI must provide relevant data and analytics to adapt quickly to business needs. While the business needs agility in implementing new solutions and making changes to existing solutions, IT organizations are becoming bottleneck in meeting demands and adapting to the changes. There are three key needs here: agility, flexibility and reduced dependency on IT.
Why is Self-Service BI More Important Now?
In last decade there was focus on integration of systems and eliminating data redundancy. While this helped organizations in providing reliable reporting platform with quality data for analysis and decision support, it led to complexities in BI systems due to interdependencies. This made organizations introduce strict governance and change control processes. The undesirable by-product of the scenario is that BI organizations are finding it difficult to keep pace with the business needs. The budget pressure on IT has not helped either.
This means that IT may not provide answers to all business problems and questions. IT must relinquish some control to business or, ideally, enable business meet its own analytical needs.
Businesspeople have been running queries leveraging data models provided by IT for a long time, and most BI vendors provided some capabilities in this area. However, the business demand and IT limitations mean this must now be extended further to include additional functionality and support a wider user base. Technological advances in the BI marketplace make this concept viable. Most product vendors now offer robust capabilities by offering tools that are now more intuitive, require less training and provide added functionality that makes analysis easy and fast.
What is Self-Service BI?
I've come to an inclusive definition of self-service BI:
Self-service BI is a combination of tools, technologies, processes and best practices that helps businesspeople perform data analysis in self-sufficient manner, leading to improved adoption of BI. The IT department plays the crucial role of service enablement and continuous improvement of BI services to support flexible analysis of internal and data.
Thus, the key attributes of self-service BI are:
- Ability for anyone to generate analytics/reports,
- Reduced IT involvement,
- IT-enabled access to data, leading to flexibility,
- Tools with interactive, intuitive, personalized features
- Optimized robust processes, best practices and a governance model for continuous improvements,
- Reduced time for deployment and changes.
Successful Self-Service BI Adoption
While self-service BI may appear as a panacea for the problems outlined above, organizations need to ensure that they are equipped for successful implementations. The four pillars for successful self-service BI adoption are technology enablers, process maturity, best practices and the right mindset (see Figure 2 at top left).
When selecting the proper tool, businesses should have functionality and scalability in mind; without these attributes, self-service BI may not yield desirable results. A tool should have rich and intuitive functionality that businesspeople can leverage and use to build what they need. A tool that does not provide strong base functionality requires a lot of effort to produce desirable reports/dashboards and will not serve the cause. Some high level key features are:-
- Templates for reports and dashboards,
- Intuitive features for report creation, e.g., wizard based, prompts, good online help,
- Rich visualization features,
- Search capabilities,
- Data federation to support data analysis from multiple systems,
- Integration of unstructured data,
- Personalized view,
- Collaboration features.
In-memory databases will support large analysis and rapid query response. As the design of the underlying data models may not have been suited for the analysis that users will perform, an in-memory solution and integration will help meet the performance needs.
It is also important to have a rich semantic layer (metadata documentation) to enable the business. The success of self-service BI depends on how you enable businesspeople to leverage what is already present in BI. Thus, a rich metadata layer that is business-user centric and user friendly is required.
Self-service BI will not be successful if organizations do not have the right processes defined to leverage it. The key points to note are:
- Well-defined roles and responsibilities between IT and business: This helps clearly set expectations upfront. The service levels from IT must be defined as well.
- Data stewardship: Data governance becomes especially important because the business will be increasingly enabled to use the data. Ongoing data quality checks,, preferably automated, become useful. Additionally, data security processes must be identified to ensure that data is controlled with clearly defined ownership and that there is a process to make it available to as needed.
- Chargeback models: IT will still invest time and money once the solution is launched. Hence, chargeback models for cost must be defined to ensure that appropriate business units pay for the services they are getting.
- Clearly defined areas for report enablement: It is necessary to define the difference between IT-developed reports/dashboards and business-enabled self-service before launching the self-service strategy. Typically, it is recommended that IT should enable reports that are widely used across organizations, thus standardized. Also, reports for statutory and compliance purposes should be enabled by IT.
- Standardization of KPIs and a dictionary to ensure single version of truth: An undesirable fallback of businesspeople producing reports is that it can lead to data manipulation at the hands of users, and standard KPIs produced by a different group may show different values as a result. To avoid this, the corporate standard KPIs and dictionary should be defined.
- Governance and change management: There must be joint governance of BI by business and IT. As part of the governance model, organizations should define change management processes and also address compliance needs.
Following Industry Best Practices
BI organizations must continuously evolve, striving to follow the best practices in this area. These actions can include:
- Driving a culture of continuous improvement,
- Sharing best practices in usage by driving a culture of collaboration and knowledge sharing
- Providing the right level of business documentation
- Establishing a strong power-user community
Change in Mindset
- Drive culture of self-help within business teams
- IT needs to act as an enabler
- Provide the proper training with right level of details
- Pro-active support with data enablement
- Enable best of breed technological solutions and continuous technological improvements
Methodology for Self-Service BI
We recommend the following methodology for implementation (see Figure 3).
Organizations need to assess if they are already prepared to undertake the journey or if they need to streamline processes, implementing enablers before they can start. In this phase, you will define a plan for setting processes, enabling the proper technology, performing prototype for a business group/region and then rolling it out to the entire business. It is important to have clear goals and objectives in mind before you plan. You must involve the business, including senior executives, in this exercise to understand expectations and roles throughout the process. Without business involvement, the initiative will not succeed. Also you need to define indicators for measuring success, which can be used to monitor and quantify improvements..
Self-service BI requires robust processes and governance. In this phase, you need to define processes that will be the foundation for successful implementation. The key areas include governance structure, roles and responsibilities between IT and business, data stewardship processes, support processes with acceptable service levels, cost chargeback model, security policies and processes.
Implement Enabler for Self-Service BI
Enablers include the proper technologies and tools to support self-service. Here, you need to select and implement tools that will support desired functionality and features. You will also need additional things such business metadata layer, security and data quality frameworks, including a master data framework.
Measure and Improve
Any BI implementation is a journey with no finite end. Hence, you need to monitor performance on predefined metrics and try to improve on them, when necessary. You need to get feedback from end customers, check BI adoption throughout the organization and address subsequent needs. Also, you need to bring in industry best practices, incorporate lessons learned from implementation, as well as from the marketplace.
Self-service BI is here to stay. While the benefits are enormous, organizations need to have a clear vision, strategy and roadmap for implementation. With the methodology described in the article, you can make this journey successful. Unleash the power of self-service BI in your organization and enable your business to make insightful and timely decisions for succeeding in today’s competitive marketplace.
Nitin Kulkarni is currently working as a Principal Consultant with Consulting and Systems Integration unit in Infosys Ltd.