By Arvind Purushothaman, VP – Data & Analytics, Virtusa Corp
In the Big Data world where there are several new sources of data and new business models that rely on the intelligent use of data, it is important to acknowledge the need for a Chief to manage this. Given the multiple technology driven initiatives undertaken in organizations, the Chief Information Officer is unlikely to have the bandwidth to provide the attention the data initiatives need, leading to the creation of the office of the Chief Data Officer.
The most commonly stated reasons for having a CDO in the office is to ‘recognize the use of data for competitive advantage which include building advanced analytics capabilities’, ‘to fast track digital transformation’ and also to keep a check on the ‘increasing regulatory requirements’.
According to Gartner, “by 2018, more than 50% of large organizations globally will compete using advanced analytics and proprietary algorithms, causing the disruption of entire industries”. This inference is completely in line with the factors that are leading enterprises towards a data driven culture – like data personalization, data compliance, data uncertainty, and digital transformation. These primary factors, along with several secondary factors, are influencing organizations towards building an office of the CDO, with bigger objectives in mind such as making better decisions, providing right information at the right time to the right people, removing the roadblock of a single version of truth towards single source of truth, creating better data alignment, fixing data quality, and improving data agility.
The Role of a CDO
A Chief Data Officer can add significant value to the organization. These are some of the key opportunities for a CDO to make the organization more data driven:
1. Build an Enterprise Information Strategy working with the CIO and the business to align and drive
2. The data strategy with organizational goals
3. Act as a champion and change agent in leading organizational change required to create and
sustain enterprise data and analytics capabilities
4. Lead the effort to ensure that data and analytics are integrated into the business strategy and
roadmap
5. Act as a thought leader in the use of data in emerging digital business models and technologies
6. Lead the process to identify and evaluate internal data and analytics capabilities especially in emerging areas to improve competitive positioning
7. Work with board members and C-level executives including the CIO and CXO to create a digital business vision for the enterprise
8. Partner with Legal and Information Security teams in the organization to ensure data is safeguarded through effective data governance policies
9. Define and report metrics that represent progress against data and analytical goals
10. Build a core team of analysts, technologists who stay abreast of trends in the Data space, build POCs that can be expanded to the enterprise
The challenges
Let’s look at the typical data related challenges at an organizational level:
• lack of data governance leading to creation of data islands and point-to-point integrations
• lack of trust in the data
• lack of a data quality mindset
• fixation on data ownership
• internal resistance to sharing data
• lack of understanding of single source vs. single version
• challenges in converting data into insights
• SDLC processes hampering agility
• obtaining funding for data initiatives
• collaborating with other CxO’s
To convert the challenges into opportunities, the CDO’s should look at the following –
Track Data As An Asset
Organizations extensively talk about data being a critical asset and being data driven but rarely track it as an asset. This needs to be addressed as a high priority since organizations can reap significant benefits if they do so. One reason could be that it is difficult capitalize Data from an accounting standpoint but Data clearly meets standards associated with an asset – “owned & controlled”, “exchangeable for cash”, “probable future economic benefit”. Moreover, from a Financial Accounting standards perspective, Data should be managed as an intangible asset. Hence, the CDO’s should look at getting Data the attention is deserves by tracking it as an asset.
Monetize Data better
Data Monetization can help an organization discover a gold mine underneath. Indirect data monetization is already happening leading to – improving efficiencies, development of new products & markets, new partner relationships etc. Monetizing data requires an enterprise mindset when it comes to data ownership. A well-defined approach to data stewardship with clearly called out responsibilities is important to be able to monetize data effectively.
Measure Data
Information is an asset that needs to be measured regularly. We can look at this in 3 ways – Realized Value – that you are realizing through use of Data, Probable Value – if you can execute your plans to leverage data, and Potential Value – if you can monetize data in additional ways. If this is not done, there could be a big gap between the current, probable and potential value which you may not be aware of. The difference between the Probable and Current Value is the Information Performance Gap. The difference between Potential and Probable Value is the Information Vision Gap. For a CDO it is imperative to close these gaps and measure these values periodically to ensure progress.
Leverage new data sources and use cases
There is a strong tendency among CDOs to only look at the enterprise data within their respective organizations or data within their respective industries. This is likely because there is a strong need to derive value from existing data sources which is good, but CDO’s should also look at newer sources and ways to derive value from how data is being leveraged in other industries. Some of the additional data sources that a CDO should include are social media, email, reports, contracts, mobile, sentiment, news, blogs and Internet of Thing. As rightly said, “your biggest database isn’t the one you own andmanage, it’s the one you don’t – the Internet”.
Manage “Single Source” and “Single Version” ofthe truth – Realizing and understanding the difference between “Single Source of Truth” and “Single Version of Truth” is extremely critical for a CDO. If not understood properly, this could lead to serious ramifications on the overall enterprise information strategy, and slow down decision making. The data can have multiple versions, since data is always evolving in nature, so being fixated on one version of data would restrict the decision making of your enterprise.However, if you have a single source of data, for example, a data Lake, then accommodating customer requirements and business decision becomes easier and adds agility to the organization.
Data Governance, Stewardship and Quality
As organizations start leveraging data heavily in decision making, it becomes important to provide details about -source of the data, the quality of data, transformation rules, frequency of refresh etc. Building enterprise Data Quality dashboards and gamifying it should help bring a quality mindset and go a long way in improving the overall
data quality in the organization.
Regulations and ethical use of data
Though CDOs are not directly responsible for all the use cases leveraging data, it is still important for them to broadly understand how data is being leveraged. It becomes important for them to don a data ethics hat and work with the broader organization to ensure that the potential uses and management of information are not going to result in lawsuits or negative publicity. It is important to remember that information cannot be depleted, can be easily transported, is highly fungible, which means that it has characteristics unlike other organizational assets that allows for it to be misused more easily.
Moreover, besides ethics, CDOs should also bear in mind the information regulations and the pressures from Government they may face in case of information breaches. In the wake of recent data breaches through application vulnerabilities, it is incumbent on the CDO to work closely with the Information Security teams to ensure data is not accessible to hackers even if they are able to access servers. It is important for CDOs to manage these regulatory and compliance aspects of data along with ethics.
To overcome the challenges discussed above it is important that to have an alignment between the “C” level executives. A clear understanding of each other’s roles and responsibilities is key to organizational success. While this is true of all “C” level roles, it is more important as the office of the CDO is relatively nascent and their mandate is evolving. Ensuring communication and alignment among an organization’s C-Suite is imperative when implementing transformational programs. A Chief Data Officer should work directly with the business leaders to understand the data requirements to run their business in a better way, the frequency of the data refresh, any data quality issues and carve out programs to address them.