Skip to main content

The CDO superhero and its nemeses

(Image credit: IT Pro Portal)

The Chief Data Officer (CDO) has officially arrived, and with it, expectations to fill superhero status by leading organisations’ efforts to becoming truly data-driven. In fact, according to a study by NewVantage Partners, 55 per cent of organisations already have a CDO in place and 80 per cent of executives believe the CDO will be responsible for driving innovation and building a data-driven culture. Will this CDO superhero be able to overcome their nemeses and fulfil the innovation promise?

As our CDO superhero strives to build a data-driven culture to spark innovation, they have three hurdles (villains!) in their way: data integration, bad data and a zero-based budget.

Villain number one: Data integration

According to Forrester, the majority of organisations cite integrating data as their number one challenge. And organisations have been struggling with this concept for decades.  Building a single, comprehensive, quality view of a data subject has been a business initiative since the early 1980s and continues to elude technical and business communities today. One main challenge to integrating data is an organisation’s technology environment.

Data is everywhere across the organisation—it’s in different systems, locations, with different schema’s and with different database dependencies. Each system has a different owner, thus the data is created and managed differently. Data enters the organisation in multiple places and is duplicated and copied across the ecosystem. Information is being used by many different data users, all making changes to suit their needs. Considering the diversity and complexity of their data landscape, it is no wonder the CDO must calm the Data Integration nemesis. 

How can our CDO superhero calm their Data Integration nemesis? 

Overcoming Data Integration challenges calls for superhero powers. The best approach I’ve seen for overcoming these challenges is to implement a data strategy supported by data governance and data management. An effective data strategy should be designed to improve the way you acquire, store, manage, share and use data with five critical components:

1.Identify. Identify data and understand its meaning regardless of structure, location, or origin.  It is important to note that establishing consistent data element naming and value agreements is core to using and sharing data, and these details should be independent of how the data is stored or the physical system the data resides.

2.Store. Persist data in a structure and location that support easy, shared access and processing.  The goal is to store the data needed by the data consumers once and provide a way for people to access the data they need in a secure way. Making copies of the data results in expensive overhead, misalignment of data and potential theft of sensitive information.

3.Provision. Package data so it can be reused and shared, while providing rules and access guidelines for the data. Provisioning data is a turning point for a data-driven company because the data is packaged and shared in a way that data consumers can leverage the right data at the right time for their business processes and decision-making requirements.

4. Integrate. The bullseye of this component is to move and combine data residing in disparate systems and provide a unified and consistent data view. For this to happen effectively, there must be a methodology and approach in place to create a unified view of the data across an ecosystem managed by the CDO. Integration silos must be broken down and data development must become a disciple within the organisation. This leads us to our last component.

5. Governance. Governance establishes, manages and communicates information policies and mechanisms for effective data usage for the company. The reason for establishing a strong governance process is to ensure that once data is decoupled from its native environment, the rules and details of the data are known and respected across the enterprise. It is important to remember that the purpose of data governance isn’t to limit data access, but to ensure data becomes easier to access, use, share and is treated like a corporate asset.

With a data strategy supported by data governance, our CDO Superhero has defeated their first archenemy: Data Integration.

Villain number 2: Bad data

According to Forrester, 70 per cent of organisations feel poor quality or inconsistent data impacts their abilities to make decisions. Furthermore, an Experian study found that 72 per cent of global organisations say data quality issues impact customer trust and perceptions.  With all this discontent around the accuracy and quality of data, it is no wonder bad data is our superhero’s second nemesis. 

How can our superhero overcome the Bad Data nemesis?

Governance is necessary to defeat this villain. Because governance establishes, manages and communicates information policies about data to the corporate community, data governance addresses what are the correct terms and values for the data. It will ensure that the data being used by the data and business community is adhering to the corporate standards. Governance will also provide a mechanism for understanding the health of the data, which in turn will instil trust of data being used for decision-making functions. Governance establishes processes for addressing data that doesn’t meet corporate standards and provide processes for remediation for improving data standards. In addition, governance will provide clear ownership for the data, so the corporation knows who to contact about the data.

Once the governance foundation is put into place, Data Management is the enabler of the governance program. Data Management provides the technical foundation for managing the governance programs, maintaining and adjusting the data to meet corporate standards, providing a mechanism for remediating data, and delivering a visual representation of the data lifecycle for auditing, impact analysis and change data capture functions.

Now that our superhero has conquered Bad Data, our last villain is the zero-based budget.

Villain number 3: Zero-based budget

Many organisations believe and expect CDOs to work with a zero-based budget. If the CDO does not get the funding required to turn data into an asset and transform the culture of their organisation into one that is data-driven, then our superhero’s battle is infinitely harder.

How can our Superhero overcome the zero-based budget?

Don’t despair, there is good news! A recent study by Forrester states a “10 per cent increase in data accessibility will result in more than $65 million in additional net income for a typical Fortune 1000 company.”  I would venture to say that if the additional 10 per cent of data being provisioned to the data consumers and the analytical functions are made of quality, governed, and trusted data, then the net income would be significantly higher. From my experience, most organisations realise a return of investment for Data Management tools within a four to six-month period regardless of industry or size. 

But don’t take my word, let’s look at how one organisation ties it all together and how their Superhero conquered their nemeses.

University of North Texas (UNT) established a data-driven culture and quickly realised their return on this investment.  According to UNT, “take any large enterprise, UNT is awash in data. Academic data. Business data. Research data. As Assistant Vice President for Data Analytics and Institutional Research, Simon knows the potential of data to drive business and academic outcomes, like student retention rates and student transportation costs. But how does one transform the analytics culture of a century-old institution?  ‘The biggest challenge facing higher education right now is just trying to wrangle all the information in a way that can actually be used for some really strong purposes,’ Simon says.”

UNT is home to 38,000 green-clad students, enrolled in more than 100 graduate programs. Since its founding in 1890, the university has been a pioneer in emerging technology.

But like so many others, the institution was data rich and insight poor. Fundamental issues with data integrity, data management and data governance plagued the university’s analytics department, relegating data to silos and making enterprise analytics difficult.

Addressing this challenge meant starting from the ground up, according to Simon.

“Everyone wants to jump automatically to the visualisation and the pretty tools,” he says. “But the data must be addressed first. Where does it exist? How do you manage it? What’s the metadata around it? For us, getting our data in order has been our secret sauce.”

Data management software brought about a seismic shift in UNT’s analytics capabilities. Now, more than 425 business users across the university are empowered to make decisions based on the UNT Insights program housed on the university’s enterprise-wide data and analytics platform.

“The data management opportunities afforded us have been a real difference maker,” Simon says. “It was the shot of adrenaline we needed to reach our goals.”

Now that UNT has the building block for success, what does the future look like for them? Success with analytics has formed a springboard for future projects. Instead of looking externally, UNT has launched a payroll dashboard to analyse, down to pay check level, every dollar spent at the university. In addition, four new analytics graduate degree programs are being introduced to keep the talent pipeline strong.

With the right business processes, methodologies, solutions and investments, our CDO Superhero can successfully overcome their nemeses and instil a sense of hope, prosperity, trust and unity in the data they manage. Data will no longer be a by-product of the business, but the foundational element to propel the organisation to reach new heights and lead the way to a better and more informed future.  Long live the CDO!

Kim Kaluba, Senior Product Marketing Manager in Data Management, SAS (opens in new tab)
Image Credit: IT Pro Portal

Kim Kaluba is a Senior Product Marketing Manager in Data Management at SAS. She has 20 years of experience in data management, including sales, marketing and enablement. Kaluba received her business degree in marketing and management from Stetson University.