Data is the New Capital

There is a new form of capital – data.

Businesses have relied on human, financial and intellectual capital to grow and compete over the last few centuries. Data is a new form of capital which is just as essential for businesses to survive and thrive today. That’s why I believe that every CEO must be as strategic about acquiring, growing, refining, safeguarding and deploying their data as they are with traditional business capital.

The data opportunity (and challenge)

CEOs who see data as capital can grow and ultimately reinvent their businesses to be data-driven. But the stakes are even higher. A Forrester report indicates that data-driven organizations are growing at an average of more than 30% annually. This is due to the profound opportunity to use data capital to manage profitability, improve ROI, maximize efficiencies, reduce manufacturing costs, create new products and services, improve customer satisfaction, enhance brand loyalty, help meet regulatory requirements, achieve compliance and ultimately improve lives.

"CEOs who see data as capital can grow and ultimately reinvent their businesses to be data-driven."

Yet, while most industries are information-intensive and CEOs understand the importance of data, few have truly committed to harnessing the power of data at a strategic level. And as companies find themselves challenged with everything from rising customer and patient expectations and diminishing ROI to increased regulation and global disruptions to operations and supply chains, I’ve seen most finding themselves struggling to define and implement a data-driven strategy.

To help CEOs move from intention to activation, we’ve created a prescriptive approach for transforming into a data-driven company and deploying data capital: adoption of an enterprise-wide data and analytics strategy; investment in a data & analytics platform; development of data governance and management processes; and building a culture that promotes data literacy and engagement.

1. Develop and adopt an enterprise-wide data & analytics strategy

Corporations must develop an enterprise-wide strategy linked to every aspect of their business and informed by the overall IT strategy.

In my experience, the journey is more important than the destination when it comes to data strategy. The act of developing a data strategy in itself is educational as it generates cultural support and alignment, a growth mindset, and new business ideas and priorities.

When developing your data strategy, keep in mind:

• It should be considered a cornerstone which enables future business strategies, with optimized investments in technology, people and processes.
• It should answer questions about the operating model for the data and analytics functions.
• It should determine the right balance between defensive, offensive and monetization uses of data. For example, in an industry that is heavily regulated, the strategy must balance the offense of new product R&D and customer engagement with the defense of regulatory compliance and data protection.

2. Invest in a data & analytics platform

Investing in a data & analytics platform is essential to obtaining connected and contextual data that leads to informed answers and greater insights.

In fact, the most important investment a company should consider making is in building a data and analytics platform. The platform should be foundational and enterprise-wide to allow for the interoperability of cross-functional data to maximize power. These platforms can create analytics reports, train artificial intelligence or machine learning models to hone predictive capabilities or be used for operational applications and can convert data for easy consumption and enable agile data processing.

When building your data and analytics platform, keep in mind:

• The data platform needs to be centrally architected and, based on cloud-based infrastructure to enable secure and scalable storage, processing and delivery of data as well as mechanisms to organize, integrate, share and democratize data for consumption.
• It is built for speed and adaptability, enabling the processing of complex, data-driven insights in real-time.
• It is comprised of numerous capabilities to enable the entire data and analytics ecosystem.

3. Enable data governance and management

Trust in data often creates a gap between the promise and reality of analytics investments. Companies must ensure data quality and veracity.

CEOs know how to safeguard human, financial and intellectual capital and the same must be true for data. A data breach can mean lawsuits, but also the loss of reputation and trust. I can’t emphasize this enough: data must be managed with diligence or it risks being a liability.

Data quality requires stewardship and governance processes that come from a bottom-up approach that includes data citizenship, self-help tools, clear governance around access and firewall protections. That’s why in concert with its data strategy, a company should develop clear data management and governance policies and approaches, and a transparent stature with stakeholders. To do this, companies can take advantage of advances in technology that are making it easier to catalog and understand data, increasing its trustworthiness.

In short, if data is our new capital, trust is our new currency. And when managed properly, trust can be a critical differentiator.

4. Build a culture that promotes data literacy

Everyone throughout an organization must be data literate and committed to being data-driven in their day-to-day work.

The saying goes that “culture eats strategy for breakfast” and that is true when executing a data and analytics strategy.

The commitment to be a data-driven company must permeate throughout the organization. Also, the entire company needs to become data literate—aware of what data can do to improve business processes at the grassroots levels in the company and how to make it happen. However, in an Accenture/Qlik study of 9,000 full-time employees, only 25% felt fully prepared to use data effectively and just 21% reported confidence in their data literacy skills. To help create your data-driven culture, there are tools and platforms you can utilize that can drive data literacy and adoption throughout an organization.

Still, commitment to change must start at the top. It is vital for the board, the CEO and top management to become data conversant, knowledgeable on how data can add value to the business and their current data environment challenges and aligned around data direction. Additionally, there needs to be a data champion within the company – as well-versed in the business as data and technology – with a seat at the table for discussions of company strategy, investments and key initiatives.

Change management is critical. If the culture creates resistance, then the data strategy will stall. Take the case of the algorithm that greatly improved predicting clinical trial duration. Because an internal team resisted change, it took a full year longer than it should have to get into production.

Deploying your data strategy

It is necessary to have a programmatic approach to managing change that results from the commitment to use data as capital. Once the decision’s been made to be a data capital-rich company and a strategy is in hand, there are three ways to deploy that data strategy:

• Top-down mandate
• Bottom-up coalition
• -or- Piggybacking a major strategic initiative

There are pros and cons of each approach and what a CEO chooses depends on business context, leadership talent and appetite for investments.

I truly believe in and have seen first-hand the value that the power of data capital can deliver. Here at Accenture, we know how to help companies put your data to work – read more in my full report: https://www.accenture.com/us-en/insights/technology/data-new-capital