CIOInsider India Magazine
Chief Data Officer In Demand (A Leader Who Creates Business Value From Data)
The CDO was born as an attempt to create a bridge between functional leaders who need information in real time and the IT department. In a perfect world, functional business leaders (Sales Ops, HR, marketing) want to be the masters of their information. The CDO would investigate platforms and security, and would then create an environment to allow for each individual functional user to access the information that they need. Organizations may build their businesses on data, but they don’t necessarily manage it well. That’s why Chief Data Officers (CDO) can play a valuable role in helping the organization value its data across the enterprise.
Chief Data Officer Responsibilities:
• Thorough understanding of the business and data strategy.
• Designing and implementing data strategies and systems.
• Lead, motivate and manage large technical teams.
• Overseeing the collection, storage, management, quality and protection of data.
• Implementing data privacy policies and complying with data protection regulations.
• Determine where to cut costs and increase revenue based on insights derived from data.
• Effectively communicate the status, value, and importance of data collection to executive members and staff.
• Knowledge of relevant applications, big data solutions, and tools.
That data might be customer data, data gathered from Internet of Things sensors, social media, structured, or unstructured data; anything that the organisation gathers itself of buys in from elsewhere. The CDO must ensure the data is secured and maintained, but the role is not simply about deciding the technical aspects, like whether the information should be held in a data warehouse or a data lake or master data management.
Objectives and Responsibilities of the Chief Data Officer
Strategy: The Chief Data Officer plays a leading strategic role where he defines and oversees how the business captures, maintains, and applies data and information in order to support key business processes.
Leadership/Supervisory Role: The Chief Data Officer is in charge of overseeing the larger Data and Analytics department. This is inclusive of the Data Analytics and Data Science departments. He will oversee the development of new data analytics capabilities across the business and manage on-going comprehensive data analytics.
Analytics: The Chief Data Officer plays an analytical role where he defines and drives all analytics and business intelligence initiatives in the Data and Analytics department. The Chief Data Officer defines appropriate analytical models necessary to support use cases such as customer segmentation, among others and leverages the power of predictive insights and analytics.
Collaboration: The Chief Data Officer plays a highly collaborative role and in this position, he will oversee cross-functional data governance while simultaneously ensuring adoption and adherence to data quality and process governance in the relevant collaborating departments.
Knowledge and Opportunity: The Chief Data Officer acts as an authority within the Data and Analytics department, promoting the use of industry leading trends and new data management technologies. He is also responsible for finding data analytic opportunities for the business and ensuring data and information compliance with the business policy and external legal requirements.
Required Qualifications of the Chief Data Officer
Education: The Chief Data Officer has to have a Computer Science Graduate, Data Science, Management Information Systems, Statistics, Analytics or any other related field. An equivalent of the same in working experience is also acceptable for the position.
The chief data officer plays a leading strategic role where he defines and oversees how the business captures, maintains, and applies data and information in order to support key business processes
Experience: A candidate for this position must have had over 10 years or working experience in a senior Data Analytics or Data Science position within a fast-paced and complex business setting.
Communication Skills: Communication skills are an absolute necessity for the Chief Data Officer who oversees the Data Analytics and Data Science departments, making up the larger Data and Analytics department. The Chief Data Officer will also play a highly collaborative role where he will interact with stakeholders, departmental heads and leadership, as well as other executives. These collaborations will be a determinant of the efficiency in application of data analytics across the business; therefore, he must be capable of tailoring messages in a clear, concise, unambiguous, engaging, and convincing manner, understandable even by non-technical department personnel.
Interpersonal Skills: A suitable candidate will also be a result-driven individual, be highly creative and analytical, be a strategic thinker, have an ability to work comfortably in a collaborative setting, be comfortable working with business top-leadership and executives, be a highly organized, have an ability to work on multiple simultaneous projects and meet tight deadlines, and have an innate ability to remain calm and composed during times of uncertainty and stress.
Leadership/People Skills: The Chief Data Officer must also possess strong leadership, being able to move cross-functional groups in a unified direction as well as being able to move business executives and stakeholders. The Chief Data Officer must be a likable and approachable person who inspires trust and confidence in others who will readily give credit in his insights, judgments, and readily following his directives.
Companies invest heavily in to IT technology platforms and expect that software will produce desired result, however the best technology platform is of no use without right skill of people at every level of organization, and they are the real drivers to convert all analytic data in to useful information. Appointing Chief data officer is a first step for moving toward digital transformation and enable management to take decision through system; next step would be building up artificial intelligent to take or propose decisions based on various inputs.
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