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Top five worst practices for BI and analytics

By Marilyn de Villiers
Johannesburg, 14 Mar 2019
Melissa Treier, VP of corporate sales at Information Builders.
Melissa Treier, VP of corporate sales at Information Builders.

One of the best measures of the success of a business intelligence (BI) and analytics project is the number of people who adopt the technology and embed it in their operational practices.

However, it is estimated that only between 17% and 22% of people who could benefit from the insights generated actually do so.

This is according to Melissa Treier, VP of corporate sales at New York-based BI, data integration and data quality solutions software company, Information Builders, speaking at ITWeb Business Intelligence and Analytics Summit 2019, in Johannesburg this week.

According to Treier, the key to achieving BI success by making it accessible to everyone starts with generating insights, then operationalising those insights and being able to place a monetary value on the benefits gained.

The goal is to turn data into actionable insights with real business outcomes.

However, there are several common mistakes organisations make when rolling out BI and analytics projects that result in their investments ending up as shelfware: unused, forgotten and representing missed opportunities.

Depending on users to operationalise insights

Very often when an analytics project is developed, it stops at the point at which insights are attained. There is no strategy to get these insights to the individuals who can benefit from them, and this includes individuals who are not directly employed by the organisation, such as suppliers, partners and even customers.

However, simply getting the information to the potential users is not enough; thought has to be given as to how to encourage them to actually use it and that requires embedding the insights into what the potential users are already doing and the technologies they are already using.

Expecting self-service to address all needs

When developing self-service tools, the focus is generally on tools that are easy to use, enable data discovery and require little or no IT input.

However, despite the widespread availability of BI self-service tools, pervasive BI and analytics remains elusive, with only around 30% of all employees adopting it, let alone suppliers, customers and customers who just cannot be bothered.

The key to greater BI adoption is to actually get the people to use the self-service tools by giving them what they want in the way that they want it. Instead of focusing on ease of use when developing the tool, the focus should be on developing tools with the flexibility to put the right information in front of the right people at the right time.

Underestimating the importance of data preparation

The success of BI and analytics starts and ends with data. However, there are many challenges in the way of getting the data required for a successful BI and analytics project: it may be spread across too many apps and systems throughout the organisation; and there could be multiple versions of the truth; the data might be outdated or simply not timely enough; and the technology itself is not able to meet needs.

However, one of the most important data challenges is having data that is clean enough to use. While most people are prepared to live with poor data quality and try to work around it, this is not sustainable. BI and analytics has to start with clean data.

Using tactical BI tools to support broad BI strategies

Many organisations opt for BI tools without considering what the users really want and are able to work with. Technical users are sufficiently proficient to work with BI tools; non-technical users - the bulk of the potential users - are only comfortable with the ease of use offered by apps.

If IT continuously gives users the information they require in formats they do not understand, such as complex dashboards that require further interpretation, they will simply stop using it, and even start to distrust analytics.

However, giving them information in an easy-to-understand graphic is also not the answer. Users need to be engaged and BI apps, therefore, should be dynamic and enable interaction.

The success of BI depends on close collaboration between the technically proficient in IT on the one hand, and the ordinary business users on the other.

Ignoring important data sources

It's been estimated that 90% of all data currently available was generated only in the past two years. It is important therefore to tap into all the available data to obtain the depth of insights that are required to make people want to use the system.

The first step is to have a strategy for integrating structured and unstructured data in a way that makes sense for the organisation.

"BI and analytics success is not an event, it is a journey, and adjustments and enhancements must be continuous to ensure it continues to be used," Treier concluded.

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