Editor's note: The following is a guest article from Dina Kholkar, global head of analytics and insights at Tata Consultancy Services.
Data democratization has been a hot topic among chief information officers (CIOs) and chief data officers (CDOs) for some time, but the acute need for it is now part of today's board room discussion. Data and universal access to it, is touted as the key to transforming companies, creating new opportunities and unlocking the value embedded within organizations.
But the truth is, data democratization has not been the panacea people envisioned. Why? Because most companies are still struggling to achieve it. Recent studies suggest rather than making progress, many firms actually are falling behind in meeting their data goals.
In fact, in a 2019 Big Data and AI Executive Survey by NewVantage Partners, technology and business executives from corporations such as American Express, Ford Motor Co., General Electric and Johnson & Johnson admitted they weren't where they wanted to be on the road to data democratization.
For example, 72% said they didn't feel they had created a data culture yet – the kind of culture necessary to boost data democratization. Furthermore, 53% said they are not yet treating data as a business asset and consequently felt their enterprises were not competing on the analytics front.
So, how can companies democratize data and enable anyone in a company to have access to information and use it to make faster decisions, improve customer experiences, drive operational efficiencies and generally improve the bottom line?
Not surprisingly, the answer doesn't lie in the technology; that's the easy part.
The answer lies in managing the human side of the equation. In the same survey, a whopping 93% of participants cited people as holding back the progress of digital democratization.
Digital democratization pushes organizations to rethink how they manage, distribute and interpret data. That often means driving a dramatic cultural change in the organization. It also means freeing information from the silos created by internal departmental data, customer data and external data and turning into a borderless ecosystem of data.
One of the most common obstacles organizations face is making the data truly accessible. People are risk averse and fear shared information might be used inappropriately or fall into the wrong hands.
Consequently, better data governance practices are needed to coordinate security, data privacy and regulatory issues and convey that information to all parties to alleviate concerns.
These practices should be based on the following six factors:
- Ethics: Assessing and publishing the intent and basis for data collection and sharing and frequently monitoring this intent, is critical.
- Privacy: Adhering to privacy norms to protect personally identifiable information is key in maintaining stakeholder confidence.
- Trust: To avoid facing a "trust deficit," issues related to trust must be identified and managed with the entities in the data value chain including regulators.
- Legal: A dedicated legal team focused on democratization activities should be appointed to oversee regulations and data-related legal risks.
- Risk: An action plan to reduce the impact of risk will strengthen democratization success.
- Valuation: Democratization should only be undertaken if it will add brand value, honor security and moral values and the principles can be monitored.
By employing these, the payoff becomes substantial. No field today may better exemplify the benefits of achieving data democratization and governance than healthcare.
Drug development, for example, is one of the business world's most regulated, expensive and risk-laden processes. On average, it costs roughly $2.7 billion to bring a new drug to market, according to a Tufts University study.
Democratizing data by creating a shared framework of metadata across clinical trial phases can give researchers real-time data and ensure a seamless exchange of information across all phases within and outside the company.
Boehringer Ingelheim has used such techniques to achieve better, faster data flow in its clinical trials and accelerate its drug launches — while still achieving better regulatory compliance. So democratizing data has helped ensure privacy and security, even while speeding the delivery of life-saving therapies to market.
Being able to easily see relevant information is also essential to a successful data democratization program. Data users shouldn't have to become data scientists to benefit from data, they should have access to it in various forms to encourage consumption.
For example, microservices, reports and dashboards provide plug and play options for non-data specialists to understand different data stores. Visual analytics — infographics, interactive reports and even augmented and virtual reality — are growing in popularity among enterprise users. Finally, using conversational systems and simply asking for the answer has never been easier.
These conversational systems are changing our expectations and interactions with machines and are making democratization possible.
Take the case of an Australian oil and gas company. The firm realized it had decades of priceless information about equipment maintenance activities within its organization. But no one was certain who had it or how to share it.
In spite of having plenty of logistical data, the company struggled to identify train availability to transport its liquid natural gas. This was critical to improve asset reliability and availability, as well as reduce maintenance, repair and replacement costs.
So, the company culled information from various departments and created a new simulation model that all departments could understand and use to improve system performance.
The company also began regularly compiling the data and enabling access to it through an app. This allowed employees to share information on their part of the business and discover information from other departments at the click of a button, creating new communities and new business goals. Ultimately, democratizing data changed business behavior.
Conversely, a new business opportunity may necessitate democratizing data to realize its full potential.
A major business-to-business steel company recognized it was going to have to shift to more of a B-to-C model. Driven by a government program to build 20 million affordable homes over three years, as well as a growing base of digitally-oriented consumers, the company realized it not only had unique insights into potential market demands, but also could target a whole new market of underserved customers.
The company decided to launch a steel retail store in a new online space. This gave the steel company improved customer insights thanks to the data accrued from increased interactions with clients and prospects. As a result, the organization was able to make informed business decisions, resulting in higher profit margins.
In fact, the company's new consumer-facing e-selling platform generated more than $14 million in sales during its first year of operation – gains that could not be realized without data democratization.