Are You Fluent In Data?
Amitabh Ray, Managing Director, Ericsson Global Services, 0
As a leading global player in the food services business serving 100 million people every day, Sodexo faced a huge challenge – food wastage. It launched WasteWatch a few years ago – a program to reduce food waste by 50 percent in its entire value chain by 2025. Last year, the company won the Tech for Good award at the eCAC40 Ceremony organized by Les Echos, a French financial newspaper, for already achieving a significant part of its target.
Sodexo realized that it couldn’t achieve its ambitious target unless it involved all its employees in a massive digital transformation exercise, which had to start with creating digital literacy across the organization. In other words, everyone had to be fluent in data.
It meant that they should understand the value of data and know how it was created, processed, stored & accessed for everyone’s use. The important takeaway from this project is that the organization created a ‘data-bilingual’ leadership and management team, who could connect the dots between business outcomes and data. Sodexo teams can now easily capture food waste data, giving clear insights into what is being wasted in their kitchens and why. Armed with this understanding, teams can implement targeted action to help end avoidable food waste. At the pilot sites, this program has prevented an average 50 percent of food being wasted.
So, what is data literacy or fluency? Data literacy is the ability to read, analyze & understand data, and fluency is the ability to communicate using data. The First Industrial Revolution democratized the ability to read and write, which earlier was reserved for the wealthy only. Similarly, data literacy is an important component of the Fourth Industrial Revolution, built on data, analytics, sensors and robotics.
Regrettably however, Sodexo is a rare example of a data-literate organization. Recent global research, which includes India, shows that 93 percent of business decision makers believe that data literacy is relevant to their industry, and it is important for employees to be data literate, yet less than a third see data literacy as an important factor in a successful economy. Significant skills gap exists, with just 24 percent of the global workforce fully confident in their ability to read, work with, analyze, and argue with data. According to Forrester, only 48 percent of decisions are made based on quantitative information and analysis.
Research by the global data science community Kaggle reveals that low data literacy and understanding at leadership level is a roadblock to digital transformation. Kaggle asked 16,000 data scientists and data analysts on what’s holding them back in the workplace and found that three out of the top five barriers were about cultural and leadership shortcomings in data literacy. The ability to translate data into useable information that inspires action still dodges many of us; widespread data skills do not exist across today’s workforce, data is not democratized, and data-driven decision making is still a rarity.
Business users need quite simple information, presented in an easily digestible way that allows them to make better decisions. The idea that a frontline customer-facing employee needs to spend a lot of time analyzing information, is just not helpful if it doesn’t directly contribute to how they do their work.
It is impractical for organizations to ask employees to retrain as data analysts/scientists. Instead, data should be built into the workflow and made accessible through the regular devices they use, like mobile phones. Once data is on the fingertips of employees in a user-friendly understandable way will an organization become data literate.
Tools incorporating data into existing workflows and decision making processes enabled via embedded analytics have been around for more than a decade, but adoption has been slow. A fool with a tool will remain a fool, the old saying goes. It is important to demonstrate that data driven decision making is solving real life challenges.
It should begin with decentralizing data. Traditional leadership and management feel powerful to control access to data, but this must change. Individuals must have access to necessary data to make decisions. Resources must be directed towards supporting initiatives that ensured insights are captured and presented in a way that supports data-driven decision making. If data is our most important asset, then we need to innovate a way to have it reflected in the valuation of the organization. Enterprises must have equal focus on data workers – those who use data and analytics to take decisions – as much as on data scientists; this will be the foundation of digital transformation.
Data literacy must be top priority for organizations; the end goal is for everyone in the organization to have the confidence to analyze data and make their own decisions. Data literacy will lead to data curiosity, and curious organizations will be the successful survivors in the Fourth Industrial Revolution.
The idea that a frontline customer-facing employee needs to spend a lot of time analyzing information, is just not helpful if it doesn’t directly contribute to how they do their work
Business users need quite simple information, presented in an easily digestible way that allows them to make better decisions. The idea that a frontline customer-facing employee needs to spend a lot of time analyzing information, is just not helpful if it doesn’t directly contribute to how they do their work.
It is impractical for organizations to ask employees to retrain as data analysts/scientists. Instead, data should be built into the workflow and made accessible through the regular devices they use, like mobile phones. Once data is on the fingertips of employees in a user-friendly understandable way will an organization become data literate.
Tools incorporating data into existing workflows and decision making processes enabled via embedded analytics have been around for more than a decade, but adoption has been slow. A fool with a tool will remain a fool, the old saying goes. It is important to demonstrate that data driven decision making is solving real life challenges.
It should begin with decentralizing data. Traditional leadership and management feel powerful to control access to data, but this must change. Individuals must have access to necessary data to make decisions. Resources must be directed towards supporting initiatives that ensured insights are captured and presented in a way that supports data-driven decision making. If data is our most important asset, then we need to innovate a way to have it reflected in the valuation of the organization. Enterprises must have equal focus on data workers – those who use data and analytics to take decisions – as much as on data scientists; this will be the foundation of digital transformation.
Data literacy must be top priority for organizations; the end goal is for everyone in the organization to have the confidence to analyze data and make their own decisions. Data literacy will lead to data curiosity, and curious organizations will be the successful survivors in the Fourth Industrial Revolution.