Take an issues-driven approach to business intelligence

Accenture advises CIOs to put business issues ahead of data, know the users, look beyond ERP data, and embed analytics in BI

Companies find themselves surrounded by data, but struggle to extract the true “intelligence” their business intelligence systems promise. They should consider a new approach that Accenture describes as “issues-driven business intelligence”.

Business intelligence, or BI, has a very broad definition and use in the market. 

Depending on analytics skills level, technology capability, and business objective, organisations apply BI in a variety of different ways – ranging from a single query in a marketing department, to exploring new business opportunities in a country/region, to uncovering enterprise-wide operational efficiencies.

However, no matter what type of BI a company pursues, or the business need it is trying to solve, the main BI goal is to find the right insights at the right time and place, to improve and optimise decision-making and organisational performance.

Seeking guidance from business data

In Accenture's experience, the BI reality is a far cry from this concept. Too many executives think of BI as a static Excel file, with rows of data and little in the way of context, let alone real guidance. But shouldn’t they expect guidance from their data instead of mere numbers?  

Take a global seed company with an enterprise resource planning (ERP) system, which dutifully provides information on weekly seed sales, compares this with the year prior, breaks it down by client, and so on. 

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When a sudden plunge in sales hits a certain region, management does not know why. There is no insight noting this area was hit by a heatwave that caused water tables to drop and crops to wilt. Quite simply, there is no context explaining the specific root causes or issues behind the shift in the sales pattern.

Lack of context can affect a business in various ways. For instance, according to an Accenture study 58% of respondents identify “outcome from data” as a key challenge. Plus, key executive decisions still rely more on intuition than on proper data-driven analysis.

How can businesses achieve the “intelligence” that will lead to opportunity and outcomes? They need to focus on what Accenture terms “issues-driven business intelligence”. 

At its core, this approach is about making sure an organisation’s data is an asset to the business – having the right data, at the right time and place, and displaying it in the right visual form. Through this, data-driven decisions can be made on the intelligence garnered, and confident actions can be taken to pursue desired business outcomes.

Characteristics of an issues-driven BI approach

  • Start with questions addressing the business issue, not the data
    Issues-driven BI starts with identifying strategic questions relating to a business problem. This may sound banal, but it is hard work. Companies need clarity about what matters most: why is market share shrinking in one place, but rising in another? Or how will pricing pressures affect profits? Then they can start designing issues-driven BI solutions and identify the key data that will give the answers they need.
  • Know your users
    The main BI goal is to find the right insights at the right time and place, to improve and optimise decision-making and organisational performance

    Narendra Mulani, Accenture Analytics

    Issues-driven BI requires companies to embed their business intelligence within the actual business process being assessed, rather than trying to conduct it in isolation elsewhere. The BI team needs to know their users and how timely they need reports, their core goals (along with the larger business objectives as a backdrop), how they can use the reports produced, and what changes would be most material for them.
  • Look beyond ERP and to new tools and techniques
    Issues-driven BI goes beyond ERP data and engages multiple data sources from within the business and externally. To assist CIOs with analysing old and new data types, a new generation of big data-centric analytics tools are available to digest the new types of unstructured data and find the patterns and correlations between the data. An added benefit to using big data for BI is that real-time results can be uncovered due to the streaming nature of most big data types, for example information from social media and machine-to-machine communication. New visualisation techniques are also emerging that bring information to life (e.g. plotting trends against digital maps).
  • Embed analytics into BI
    Instead of having an automated BI query and report telling users what is important to look at, when analytics is embedded into BI it can provide early alerts based on patterns found in the data and provide enhanced context. Looking back at the seed example shared earlier, this was the needed and missing step. In short, embedding analytics into BI makes the system more advanced and predictive, turning the information into more actionable insights for the user, allowing them to more confidently pursue a business outcome.

Making the transition to an issues-driven approach can be hard, but there is benefit to be had. 

Issues-driven BI offers businesses the opportunity to ensure decision-makers truly get access to “intelligence”, rather than just more information, so they can make the decisions that will profit their business.

Narendra Mulani is senior managing director at Accenture Analytics.

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