Actionable data is the most critical factor in digital transformation: Mukesh Jain, CTIO, Capgemini India

Data-powered enterprises vastly outperform their peers on multiple financial measures, realizing 70% more revenue per employee and driving 22% more profits, according to a report by the Capgemini Research Institute entitled, “The data-powered enterprise: Why organizations must strengthen their data mastery.” Capgemini has found that while applying data and analytics is becoming a prerequisite for success, less than 40% of organizations use data-driven insights to drive business value and innovation.

In an interaction with Express Computer, Mukesh Jain, CTIO, Insights & Data, India, Capgemini, tells us why data-driven enterprises enjoy significant financial benefits compared to the rest, and how Indian enterprises can become data driven to achieve better success in the marketplace

Some edited excerpts:

What are some of the key findings of the report “The data-powered enterprise: Why organizations must strengthen their data mastery.”

Data-powered enterprises vastly outperform their peers on multiple financial measures on multiple financial measures, realizing 70% more revenue per employee and driving 22% more profits globally. While applying data and analytics is becoming a prerequisite for success, less than 40% of organizations globally use data-driven insights to drive business value and innovation. Data mastery is critical to gain a competitive edge and organizations that don’t take concrete steps to achieve this will struggle to keep up.

Only one in six (about 16%) organizations can be categorized as data masters (Data-powered organizations) based on several factors of data mastery, including the necessary data tools and technologies required to use and leverage data as well as the appropriate data vision, governance, skills and culture.

Organizations are making headway on data-driven decision making and actioning. The research shows that 50% of organizations globally put data at the heart of decision making. At a country and sector level, data-driven decision making is more prominent in the United States (77%), Germany (69%), and the United Kingdom (69%), and in terms of sectors, banking (65%) and insurance (55%) are more data-driven.

While progress has been made, a majority (51%) of the time, businesses still use historical data (a reactive decision-making approach), meaning they lose out on a competitive advantage. Only 23% of the time do they use predictive approaches, while 18% of the time they use prescriptive approaches and use an autonomous or self-optimizing approach just 8% of the time. Data masters enjoy between a 30% to 90% advantage in metrics across customer engagement, top-line benefits, operational efficiency, and cost savings. Major gaps exist between business executives’ trust of data and the technical executives’ perception of this trust: only 20% of business executives trust the data while 62% of technical executives believe their business users do so. Of the organizations where data is not trusted, the research found that only 24% were able to monetize their data assets in comparison to 83% where it is trusted. Poor data quality is a major contributor to this mistrust: only 27% of business executives are happy with their data quality while 54% of technical executives think their business users are happy with the quality

How different is the data strategy for Indian enterprises when compared to the rest of the world? Do you notice any uniqueness or similarities?
Data strategy for Indian enterprises are unique in nature compared to rest of the world. The investments in data lake, warehouse and move to cloud have started and it is picking up now at much faster rates than the same few years back for rest of the world companies.

While organizations do believe in the power of data, the Data Science talent availability for Indian companies is lower than other countries. Investments in R&D in the areas of Data, AI and Machine Learning need to be enhanced further. Decision makers are used to taking decisions based on past experience, for lack of data availability or quality issues. In our recent interactions with CXOs of Indian companies, we are seeing an increasing trend of more and more organizations realizing the power of data and ready to explore options and look at possibilities. The hesitation is always around costs involved in building the system from scratch and questions in mind around if it will work, how it will work, adoption across organization and ROI.

Can you share with us some of the best examples of data driven enterprises?
Some of the best examples of data driven enterprises are the following:
• Enterprises that align data & analytics strategy with their business strategy
• Organizations that have only one source of truth for data, where no other version of data is available. Everyone depending role / access would know where to find the data that is needed to make decisions.
• Organizations that make data available anytime, anywhere on any device. Broader adoption of data powered decision is possible with self-service and real-time. If somebody has to reach out to another person to get data, rate of adoption will be impacted.
• Operations review is based on data directly from automated system. This will enable higher confidence in management and lower the risk of manipulation. This will also enable anytime access to data.
• Organizations that have a Central team / Centre of Excellence and custodian of data to help drive adoption, consistency and governance. While data is everybody’s responsibility, someone senior in the organization needs to be in-charge of driving higher adoption.
• Organizations encouraging innovation in data and Data Powered Innovation. Making it easier for people to access data and bringing in innovation in their process helps getting more value from data while improving their competitive position. In my experience, I have found people to do better when they have access to data at their fingertips via self-service access.
• Organizations that enable role-based access to data, insights and outcome at the system levels, makes it easier for employees to access data and enables faster adoption which can also be scalable.

At Capgemini, we have deployed 890 by Capgemini, an activator of data analytics for an Insurance client in USA. They have confirmed, their usage has crossed 92% within 6 weeks and are able to take data powered decisions faster and have resulted into 68% reduction in claims processing time thereby improving customer satisfaction. 890 by Capgemini is available on any cloud, and with a single interface, it puts clients at the helm, ready to engage with the kind of insights that deliver real business outcomes, at speed and scale. This is a good example of giving more power to employees with data and enable them to explore everything that is needed to take informed decisions faster. These are some of the good examples of Data Driven Enterprises where decisions are taken based on data and it is part of the process resulting into tangible results.

What are some of the best practices that you recommend for enterprises in becoming data empowered?
Actionable data is the most critical factor in digital transformation. According to the Capgemini report, organizations have made headway in data-driven decision making and actioning, but the journey is far from over.

Some of the best practices recommended for becoming a data powered enterprise are below:
• Move away from HIPPO (Highest Individual Paid Person’s Opinion) culture. This acts as a major barrier to data driven decision making.
• Lead by example: start with top – when CxO talks about data, it matters a lot. This drives right behaviour across organization and fosters Data culture.
• Capture data at every part of the process and make it easier for people to interpret and alert for major deviations and thus drive better decisions
• Ensure sensitive and confidential data is handled with care and adhere to respective local laws – right people need to have access and in case of incorrect access alerting people.
• Drive Data Literacy across the organization. It is important that employees at all levels of the organization understand data, value of data and use it in day-to-day decision making
• Nurture data science skills by providing coaching and guidance to employees and provide the necessary infrastructure and tools, where they can build innovative solutions powered by data. At Capgemini, we have a program called, Millennial Garage which enables fresh graduates who join the company to get an opportunity to work on building innovative solutions in data science for multiple sectors. At Capgemini we have signed MoU with few colleges and setup “Capgemini Insights and Data Centre of Excellence”. We have contributed to and deployed updated curriculum in Data Science, Machine Learning & Artificial Intelligence. This has enabled students to gain skills on data, get hands-on practice with real data, get mentoring from senior and experienced professionals and therefore they are more ready to lead with data and deliver innovation when they join any organization.

Our experience shows when business KPIs are tied to individuals and are empowered with data, it gives better results as we are not asking for results, but also enabling them. Have one place for people to access data. A single place for people to go and access data, insights and outcomes is the starting point of being a data powered enterprise. Providing tools & access to environment for people to play around with data, perform what-if analysis and once they find some good insights – ability to publish it and make it available to enable better business outcomes.

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