How can the role of the Chief Data Officer (CDO) evolve to create business growth? Start with the framework of ‘Offense’ and ‘Defense’ to generate revenue and transform the business.
The CDO bears responsibility for the firm’s data and information strategy, governance, control, policy development, and exploitation of data assets to create business value. Source – Gartner
Chief Data Officers are a recent addition to the C-level suite and their rise is directly related to the new emphasis and focus companies are placing on their data assets. The role of the CDO is relatively new and evolving rapidly. Companies have come to realise that to ensure their data assets are protected and to maximise the return from assets they require a senior executive to be devoted exclusively to managing and protecting these assets. Even though it is a recent arrival the role of the CDO already appears to be in transition, with a shift in focus from risk and regulatory issues to activities that support business growth.
The impetus behind the role of the CDO is continuing: a recent survey by Gartner (Third Gartner CDO Survey – How Chief Data Officers are Driving Business Impact, December 2017) found that the adoption of this role is rising globally. The number of organisations implementing an office of CDO also rose year on year, with 47% reporting that an office of the CDO was implemented in 2017, compared with 23% in 2016.
Gartner predicts that by 2019, 90% of large organisations will have a Chief Data Officer.
We are also seeing companies replacing other roles in favour of a new CDO role. In January 2018 Easyjet replaced the CMO role with a CDO role, which they said, “will give greater focus and weight to the airlines use of data to improve our customer proposition, drive revenue, reduce cost and improve operational reliability”.
The Role of the Chief Data Officer
Chief Data Officers have an important job where data is the currency of opportunity. A survey commissioned by PWC to understand the factors driving the growth of the CDO role and how their mandate is evolving was very clear: the scope of many CDOs has expanded from setting policy and rolling out of foundational data management capabilities to owning platforms and actual oversight and execution of data programs. Despite this expansion in the CDO’s remit to new areas respondents are still in the process of implementing foundational data management capabilities. However, PWC found there is a strong need to obtain buyin and understanding of the CDO role across enterprise and align the role with and support business strategy.
CDO’s are the custodians of an organisation’s information assets, they must use this information as a catalyst for change, to automate business processes, understand and develop better relationships with stakeholders, and ultimately capture strategic value from data and deliver high-impact business outcomes.
The role is an enterprise wide role with responsibility for developing a vision and strategy around the protection and use of a company’s data assets. They are responsible for executing this vision and strategy. This means that amongst other things they are responsible for the following:
- Data Protection, Privacy and Security
- Data Governance
- Information Management
- Data Quality Management
- Data Lifecycle Management
- Definition and enforcement of standards
The office of the CDO is a multi-disciplinary office with professionals and expertise drawn from sectors as diverse as Compliance and IT. It is not unusual to see professionals with the following expertise in the office: Privacy & Policy Experts, Data Stewards, Data Analysts, Data Scientists, Information Architects, etc.
Creating a new mandate for the Chief Data Officer
The remit of the CDO is very broad but is changing its focus rapidly. Valerie Logan, Research Director at Gartner, says: ‘while the early crop of CDOs was focused on data governance, data quality and regulatory drivers, today’s CDOs are now also delivering tangible business value and enabling a data-driven culture’.
Indeed, the latest piece of research from PWC states clearly that the scope of many CDOs has expanded from setting policy and rolling out of foundational data management capabilities to owning platforms and actual oversight and execution of data programs.
What we are now seeing is an increased maturity in the CDO role, with a change in focus from a Defensive position where the focus was on compliance, security and regulations, to an Offensive position with an increased focus on working the data assets and generating new revenue and opportunities for the business.
It is this distinction between ‘Offensive’ and ‘Defensive’ that is set to become the defining characteristic of the role of the Chief Data Officer.
The use of the ‘Offensive’ and ‘Defensive’ approach means that CDOs can create a framework for understanding, obtain buy-in for their role and quickly align outcomes with business strategy.
Rethinking how CDO’s carry out their role: Defensive Vs Offensive
In the very early stages of creating their data strategy, a Defensive Strategy meant that the CDO was concerned primarily with preventing the risk of damage occurring in the business because of a loss or inappropriate use of Data within the business.
However, this definition is too narrow: today the CDO’s Defensive Strategy means focusing on the following:
- Creation and deployment of usage policy, security and protection policies and regulatory compliance around data assets
- Ensuring all data held within the company is of the highest quality
- Carrying out data validation as data is moved and transformed within the company to ensure quality does not degrade as this data is used within the company
- Controlling data access within the company
- Implementing data security on a granular level, allowing data to be exploited and used but within regulatory guidelines
- Practicing data life cycle management ensuring that data is fresh and relevant, that data is not stored longer than is necessary.
Adopting Offensive Strategies around data is a more recent trend. As a result, we are now seeing companies focus more on the following:
- Using data assets to enhance existing products and services
- Using data analytics to increase speed to market of new products
- Using information to boost product development
- Combining third party data with internal assets to create new assets and revenue, generating opportunities for the business
- Building a strong data foundation and a data-driven culture within the business
- Making changes in how C-level executives use data to drive culture change throughout the company
How can Bluemetrix help with ‘Defense’ and ‘Offense’?
Using Bluemetrix Data Manager with Control-M we can help in the following three areas:
Creation and Deployment of a Hadoop Data Lake:
Most Hadoop Data Lake projects take 12 months + to implement. They often run over budget and take a lot longer than anticipated to come into operation. Using our automation tools, you can have a Hadoop data lake operational and in production within 3~4 months of project kick-off. By this we mean we can do the following:
- Architect, design and deploy a secure data lake with Hadoop
- Move structured and unstructured data onto the lake and make it available for processing and analytics
- Embed Governance and GDPR compliance into all the processing so that it happens automatically in the background
- Make the data and the processing capabilities of the data lake available to business users and owners within the company
Implementation of a Defensive Strategy:
Use automation to deploy a Defensive Strategy and ensure day to day operations are operational, functioning and compliant within 3~4 months. This will include implementing the following:
Automate the Ingestion of Data
- Apply governance by default to all data ingested onto the lake
- Enable data to be ingested using a simple easy to use drag and drop GUI, removing the need for any Hadoop knowledge
Automate the Validation of Data
- Validate the data for completeness, consistency and integrity
- Validation algorithms are easily customisable and work with different data sets
- Embed the validation into the process which moves and transforms the data
Enforce and Measure Data Quality
- Record all data movement as it occurs on the platform
- Allow variable tolerance levels depending on the checks and data
- Record and store all metrics for analysis and reporting
Data Life Cycle Management
- Apply retention and expiration date to all data stored
- Automatically delete the data on a daily or weekly basis, or any time frame that is required
Record History of Data Storage and Processing
- Record all archiving of data
- Record all storage of data across the processing cycle – intermediate and final stages
- Record processing jobs, data processed, time processed, etc
Embed Meta Data into Operations
- Create and deploy meta data as data is moved and transformed
- Automate the deployment and recording of Data Governance into operations
- Build Data Governance into the movement and transformation of all data
- Ensure all data has an entity available and there is lineage applied to all processing of the entity
- Customise the data stored to ensure it is fully GDPR compliant
Deploy a Data Management System
- Deploy a dashboard to show a complete view of the data on the lake
- Provide drill down access to all metrics
- Highlight quality and governance issues with data as they occur
Apply Data Masking & Security
- Enable data masking at a table, row or column level
- Apply different types of masking depending on the underlying data i.e. apply random values, replace values with xxxx, apply rotation methods, etc.
Enable User Level Data Access
- This is all managed by the creation of correct access policies on Hadoop
- It can be tied in to meta data and masking policies
- It allows control of individual level access to the data
Implementation of an Offensive Approach:
Implementing all the preceding defensive strategies results in the following:One view of the data being available
The integration of all data into one data lake in a manner which controls quality, life cycle, etc. of the data ensures that only one copy of the data exists, and every stake holder is reading and processing the same data. The application of accuracy checks, validation checks, etc. as users access and process the data guarantees that the data is always kept accurate and up to date.Easy Access to the data
Stakeholders can now access the data in a controlled manner using the BDM/ Control-M GUI. This ensures that all relevant stakeholders can access the data they require without having to understand how the data lake works or having to involve any Developers or Administrators to help them use the system. Combining the control procedures of Hadoop and Control-M allows Bluemetrix Data Manager to provide this access.
The automation of the Defensive Strategies frees up the CDO to focus on Offensive Strategies such as the following:Develop a data driven culture within the business
Create new product opportunities
Develop new features on existing products
Create new revenue streams by combining third party data with internal data
Upsell to existing customers
To a great extent, the CDO role is about change management. CDOs first need to define their role and manage expectations by considering available resources. CDOs will gain authority when they successfully verify that their organisation can own and control its data and that it can create new, better and different outcomes.
CDOs will gain authority when they successfully verify that their organisation can own and control its data.
One of most useful frames of reference for a CDO is to think in terms of ‘Defensive’ strategies and ‘Offensive’ strategies. Using this context, the role of a Chief Data Officer becomes a lot easier to define within the organisation, enabling them to obtain the budget and resources they need to be successful within.
Bluemetrix can help a Chief Data Officer on this path: we recommend that organisations serious about improving the realised value of their information assets start by considering the use of Bluemetrix Data Manager with Control-M within their overall data framework.