Analytics and Business Intelligence in India – Key End User Insights

There are four overarching trends transforming the industry: Big Data, predictive analytics, self-service/embedded analytics, and cloud-based analytics. Common technologies/tools used for sharing analytics insights within an organization comprise of spreadsheets (MS Excel), dashboards (drillable/interactive data visualization interfaces), scoreboards (performance analysis against KPIs and set goals) and reports in PDF or html format.

ARC Advisory Group recently conducted a web-based end user survey to gain a new perspective on trends in Analytics and Business Intelligence (ABI) selection, application, deployment, and related challenges in India.

Analytics and business intelligence platforms are making headway across a wide swath of industries. Our survey respondents belong to a diverse set of industries such as oil & gas, electronics, chemicals and petrochemicals, automotive, electric power, and metals and mining to name a few. Industrial companies can benefit from enhanced insights into market demand, operations, inventory and corporate performance. Analytics provides the information to effectively manage global markets, supply chains and operations.  Over 50 percent of the respondents belong to companies with a workforce of 5000+ employees.

An information-driven strategy is one that finds hidden or undervalued information to provide a strategic advantage. The increased volume of data, along with the greater variety generated by countless new devices emerges as Big Data.  Thirty percent of the survey respondents felt that analyzing large amount of data was the biggest challenge faced by their company. Over 25 percent respondents felt scattered data throughout the organization (data not centralized) was the biggest hindrance for their company.

Traditional business intelligence solutions rely on skilled IT professionals. This is an inherent barrier to widespread BI adoption. IT managers’ skills can be used for more than just BI maintenance activities. Companies need to find tools and approaches that reduce the dependence of operational managers and business users on IT professionals.

The first step to a standardized ABI is an assessment of available BI tools and user classification and analysis. BI products should be evaluated if they can be used enterprise-wide. A majority of the responses showed an adopted policy that is standardized on one or few BI/Analytics products. Larger, more mature companies can consider implementing standardization in one go across the entire enterprise, whereas smaller companies can adopt a modular project-by-project approach.

Managers often struggle to find the right information at the right time. Faster and more accurate reporting, analysis and planning and the ability to make better and more informed business decisions are the top three main factors driving the deployment of business intelligence and analytics.

An information-driven enterprise utilizes the latest IT solutions to its advantage. For example, an information-driven manufacturing company may collaborate on the plant floor level with the help of tablets and smart phones enabling quick response, deploy applications in the Cloud, conduct supplier evaluation based on past performance, and manage outbound transportation needs with the help of advanced scheduling algorithms. Social media can be a useful tool to get feedback and to keep tabs on customer sentiment. Analytics and BI platforms enable all of these operations. Business transactions in database, documents and emails form the majority of data sources used for deployment of analytics software.

The main factor inhibiting deployment is integration issues with existing/multiple platforms. Selecting a single-integrated BI solution can reduce user resistance and implementation timeframes. It was noted that the difficulty in quantifying the ROI on analytics projects was a barrier to deployment. Having a fully quantified business case may not be viable in one go, but can eventually be realized.

Effective BI can boost sales and marketing in several ways – increase the accuracy and timeliness of sales forecasts, deploy higher-yield promotions and advertising, predict future behavior of prospects and customers. The manufacturing industry can obtain real-time data from all sources and apply advanced analytics to understand hidden structures and relationships. They can then change existing manufacturing processes as needed to take advantage of the new information.

Respondents ranked ease-of-use as the most important selection criteria of ABI technology. Ease-of-use takes two forms – for the IT department that maintains and modifies BI applications, and for the end-users who actually use the application. The ability to collect and analyze operational data in real-time as well as ease-of-implementation was also rated as important selection criteria. CRM provides updated information about an enterprise’s customer, thus enabling better and quicker business decisions.  Real-time analytics can support instant refreshes to corporate dashboards to reflect business changes throughout the day. For example, in a data warehouse context, it supports unpredictable, ad-hoc queries against large data sets and in scientific analysis, applications such as predicting the weather phenomena in advance.

Organizations are recommended to begin to act on information. Armed with new insights, organizations can anticipate changes and drive better Analytics & BI platforms for industrial applications. Other recommended practices include expanding the use of predictive analytics and developing long and short-term Big Data strategies. Plan not only large datasets, but also for unstructured data such as social media, web analytics, and sentiment analysis.

ARC Advisory group has released a strategy report based on the results of the survey on Analytics and Business Intelligence.  Please get in touch with Shruti Gandhi ( for more information.

About the Author

Shruti Gandhi

Shruti’s main focus areas are industrial process equipment and control systems. Shruti previously worked for the Process and Research Engineering division of the Aditya Birla Group. She was responsible for providing technology consultancy, process optimization, and business development for the cement subsidiary of the Aditya Birla Group. She also has research experience in the materials science and bioengineering disciplines. Shruti holds a Bachelor of Technology in Chemical Engineering from the National Institute of Technology, Surat and an MS in Materials Science and Engineering from the University of Texas at Arlington, USA.

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