Each day, month, year data is becoming more important to a company’s success. Many CEOs have realized that data can be a strategic asset through proper treatment and use. Achieving Data Intelligence is as vital as Finance managing the budget, or Human Resources recruiting talent. We’re almost at the point where data can be officially listed, even quantified, on the balance sheet as a competitive advantage.
The perception, if not the reality, is now so pervasive that it’s almost a cliché. Every company wants to be a data-driven organization and are working to accomplish their goal — diving into the deep end of the data lake, hiring data scientists and data architects to run innovation programs. Companies use data to achieve digital transformation. Organizations are building out Data Offices to manage all their data projects.
Find out how Froedtert & the Medical College of Wisconsin used Collibra to improve data governance and make quick, effective data-driven decisions.
Read their Customer Story and discover what we can do for your organization.
Only a decade ago, barely a dozen large corporations had a Chief Data Officer; today, by most accounts, that number has passed 10,000 worldwide. Their initial role had a lot to with ensuring compliance and securing all data assets. Now, their mandate is to use those assets to deliver value — as we always say, to help the organization reach a state of Data Intelligence. And through all this, research firm Gartner predicts that by next year, “The office of the CDO will be a mission-critical function comparable to IT, business operations, HR and finance in 75% of large enterprises.”
So it’s as good a time as any to ask some tough questions. Is it a rough ride from creating a data strategy to executing that data strategy? How long is it before tangible benefits emerge? When does data truly mitigate risk, how does it effectively cut costs, and when does it undeniably boost the bottom line? Is the strategy aligned with existing objectives or are square pegs being fitted into round holes? Are there use cases to allay skepticism and justify greater spending?
At Collibra, we’re in the data business — and, just like our esteemed clients, we use data to run the company. We’re growing fast, and we’re growing our data sources and formats even faster. We understand the market potential and the real-world pressures our customers face because we face them too.
So please, step into the office — the data office.
We’ve always used data throughout the company, and we’ve long benefited from data collaboration, practicing what we preach. We can testify to the value of a digitally savvy board, just as research from MIT Sloan reveals that companies with directors and members “significantly outperformed others on key metrics — such as revenue growth, return on assets, and market cap growth .” We’ve nurtured a data-driven culture, encouraged the participation of data citizens, and traveled from data governance to Data Intelligence.
And as part of those efforts, we’ve created a formal data office. Because we like to look ahead, we call it Collibra Data Office 2025.
The fact that data is created and distilled throughout the corporation doesn’t mean there’s no demarcation of ownership — again, think Finance, HR or IT. Collibra’s Data Office 2025 champions the concept of data as a strategic and competitive asset and directly increases the state of Data Intelligence. This means it:
- Develops and executes the companywide data strategy
- Identifies and rolls out a data governance framework
- Defines and monitors data policies and standards (e.g. for quality, access and archiving)
- Works to increase business data ownership and data literacy
- Facilitates a data management infrastructure
- Develops and distributes company-specific and function-focused proprietary data products
A quick caveat: Data Intelligence has universal attributes, but particular elements must also be unique to each corporate mission. As with Collibra, the data office must be adapted to each company’s unique characteristics, from broad market trends to internal politics. As a result, we see many variants, including:
- Centralized: One core group is given the necessary resources and authority to serve different constituencies. There’s a direct line to the C-suite, decision making is faster and easier, and there are cost savings. However, there’s always the risk of a bottleneck that leads to delays in meeting urgent requests.
- Decentralized: Each business group has its own data office, freeing up the function to serve particular needs and priorities — a major advantage when agility is the prime driver of growth. This arrangement typically costs more, impedes data-driven collaboration, reduces the benefits of shared standards/services/tools and hampers interoperability, such as group reporting.
- Hybrid/Federated: This approach starts with a centralized group at the enterprise level to set the high-level vision and direction, then sees particular responsibilities passing to domain-specific groups or data offices aligned with Line of Business units. This sounds optimal and benefits organizations with diverse operations, but it can lead to an overload of hierarchy.
At Collibra, we’re in constant growth mode and that’s not going to change anytime soon. We prioritize use cases that offer a competitive advantage and help us win over particular customers. We’re almost always on offense and that philosophy is best served with a decentralized approach. We focus on core activities such as optimizing analytics, orienting data management towards flexibility rather than rigid control and an enabling architecture for multiple versions of the truth over a single source of truth.
Whatever the arrangement — and it can evolve — collaboration and alignment are vital. We designed Collibra Data Office 2025 to serve the business at large, which means building solid relations with business stakeholders and clearly aligning with relevant objectives. Some functions are more data-intensive, such as marketing, which creates multiple opportunities for touchpoints and collaboration. Others need less data, but no function can be walled off — the data office is mandated to identify the right resources and ensure appropriate data use.
Let’s be realistic: We’re not going to develop the same tight connections with every individual in every constituency. However, there can be no more silos. If data is to become a strategic asset, the CDO and the Data Office — like the CFO, CTO and CISO — must be a vital presence throughout the enterprise.
Here’s how we see the data office concept playing out among our customers.
- Insurance provider: This company appointed a Chief Data Officer and a Chief Analytics Officer a few years ago, both reporting directly to the CEO. Amongst other responsibilities, they have hard targets to generate revenue using data products. One example: The company now offers insurance packages specifically based on driving patterns automatically tracked by the in-car IOT device.
- Automaker: This conglomerate, of course, has many different LOBs, each operating with some independence. It created a data office at the corporate level to drive governance across all parts of the business, and authorized data teams to find all appropriate data from an in-house catalog. The central data office interacts with company-wide data science, product development and engineering teams and many other disciplines across multiple lines of business.
- Global bank: This institution was under regulatory pressure to increase data transparency, and it went hybrid: A Chief Data Officer at the enterprise level, along with Chief Data Officers at each LOB (investment, retail services, etc.). This approach succeeds with a clearly defined organizational structure and processes, extensive collaboration between key members, and alignment on specific objectives. Despite the seeming complexity, the tight focus and strategic change management have paid off: There are thousands of data citizens who are quantifiably more productive throughout the organization.
Missed last month’s installment of Inside Collibra’s Data Office? Read Data Strategy in Three Steps now.
