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Many organizations have invested time and effort in launching a self-serve business intelligence initiative, only to find that the initiative has failed to deliver the anticipated results. When this happens, organizations often struggle to understand why and how things went wrong. There are numerous reasons for a self-serve BI tool initiative to fail or to fall short of expectations. In this article, we will discuss some of the factors that affect the success of business intelligence solution implementation. This article is the first in a two article series, entitled ‘Guarantee Business Intelligence Success’, related to the success and failure of self-serve BI Initiatives.

User Adoption

If business users are not given the incentive to adopt these tools, it is difficult to see the benefit of self-serve business intelligence across the enterprise. Poor user adoption can result from any number of issues. Users may find the tools too difficult to use, or they may find that the value of the tools doesn’t measure up to the hype. In some organizations, the IT team or skilled analysts are responsible for deciding the types of dashboards and reports users may access and the flexibility of the dashboards and access. Users have an expectation regarding ease-of-use and they will determine the feasibility of using BI tools versus the old tried and true methods. If the value of the data, analysis and decision support is not persuasive, your business users will not adopt these business intelligence tools.

Data Access

If the implemented self-serve business intelligence tools do not allow for easy integration of data sources from best-of-breed, ERP, HR, CRM, data warehouses (DWH) and other data sources, business users will quickly determine that the data they can compile and analyze is incomplete and will provide inaccurate or out of date information. If it is difficult to access tools in a mobile environment, and seamlessly access data and reports on all device types and sizes, your users are unlikely to leverage and benefit from the new BI tools.

Features and Benefits

When your enterprise considers self-serve BI tools, it must look carefully at the features and benefits of these tools and compare them to the requirements and needs of the IT organization (for data governance and data watermarking, as appropriate), and for users at all levels including executives, analysts and business users. By providing a full suite of features with sophisticated functionality, and a true self-serve environment, the organization can encourage and support data democratization. Tools like Personalized Dashboards, deep dive analytics with drill down and drill through capability, key performance indicators (KPIs), Balanced Scorecards, What If Analysis, Graphical Analysis, Alerts and Cube Management will support business users and allow them to prepare and share data across teams and to make confident decisions thereby providing numerous benefits to the organization and its bottom line.

Self-Serve Analytical Capability (see Data Discovery)

Not every business intelligence solution supports true, self-serve data analysis. If users must depend on IT or on skilled analysts to perform inquiries and provide reports, they lose precious time and may end up with incomplete data or data that isn’t quite what they needed. Because business needs change every day, there is no way to anticipate every need. If a business user can leverage his or her skills, knowledge and domain expertise to create and format reports, they will have the information they need to see trends, patterns and opportunities and to address issues before they become problems. Tools like Self-Serve Data Preparation, Plug n’ Play Predictive Analysis and Smart Data Visualization allow users to become Citizen Data Scientists and ensure that the organization will gain the benefits they expect from the new BI tool.

Data Sharing and Reporting

Self-Serve business intelligence tools should easily support data sharing to improve collaboration and teamwork and assure that everyone can see the data analysis and participate in the process. Reporting must be easy and quick with drag and drop capability to create reports that are meaningful to a particular audience and clearly illustrate the analysis, options and recommendations made by the users.

Cost vs. Benefit

At the end of the day, business intelligence solutions (like any other software or tool) must provide low total cost of ownership (TCO) and rapid return on investment (ROI) and they must fulfill the promise of the expected benefits and meet the requirements of the organization. Out-of-the-box industry and business solutions for financial, manufacturing, and other verticals allow an enterprise to quickly ramp up activity and business users can jump in with both feet. Browser-based, self-serve tools that provide mobile access will optimize usage and assure that the organization can keep moving toward its goals. Seamless upgrades and migration provide fundamental support for future growth and requirements.

Data Discovery

Finally, the organization should select a BI tool that goes beyond data monitoring and management to engage in Data Discovery. As mentioned in the Self-Serve Analytical Capability section above, the enterprise must provide an environment where business users can leverage their knowledge to analyze and build on results and gain valuable insight. By enabling data exploration and discovery, the enterprise ensures that users can find high-value ‘nuggets’ of information and look at data in a variety of ways to truly ‘see’ what is happening. Data Discovery bridges the gap between the traditional business intelligence environment and a rich research environment that will encourage user adoption and assure extreme value for the organization.

There are many reasons to consider self-serve business intelligence tools but if an organization is going to undertake this type of initiative, it is important to learn from the mistakes of other businesses and understand the various factors that will affect success. Not every so-called ‘self-serve BI tool’ provides solid support for true self-serve, data democratization. In order to ensure success in a self-serve BI initiative, the organization must include IT requirements for data access and governance and user management, as well as business user needs for sophisticated, easy-to-use, mobile tools that allow for self-serve data preparation, plug n’ play predictive analysis, and smart data visualization.

Our second article in this series is entitled, ‘ Guarantee BI Success: Achieve! Accomplish! Do it Right!’ This article discusses consider the various actions and tasks an organization should undertake to assure the success of BI tools, user adoption and comprehensive business benefits.

About Kartik Patel

Kartik Patel is the founder and CEO of Elegant MicroWeb. He originated the ElegantJ BI flagship business intelligence software product, which is a self-serve, mobile BI tool designed to support data democratization and transform business users into Citizen Data Scientists. The ElegantJ BI Advanced Data Discovery, Smarten approach to BI tools, includes Plug n’ Play Predictive Analysis, Self-Serve Data Preparation and Smart Data Visualization. In 2016, ElegantJ BI was listed as Representative Vendor in the ‘Gartner Market Guide for Enterprise-Reporting-Based Platforms’, and noted in the ‘Gartner Magic Quadrant for Business Intelligence and Analytics Platforms.’

Original Source – Guarantee BI Success: Why Self-Serve BI Initiatives Fail

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