How CIO helps company's leadership in data-driven decision-making

How CIO helps company's leadership in data-driven decision-making

Effective decision-making at the appropriate time is crucial for the sustainable growth of any organization and data is the most significant tool through which key decisions can be made whenever needed. Data contains key information such as customer behavior, demography, industry trends, and growth statistics that make it the most important asset of an organization.

Many research studies in the past indicate that data-driven companies are more like to outperform their counterparts by 6 per cent in profitability and 5 per cent in productivity. The fast-paced digitalization of business operation has further boosted the relevance of data in company’s decision-making process. Here comes the role of Chief Information Officers (CIOs) in leveraging data through statistical modeling, data mining techniques, and machine learning (ML) to make smart decisions.

In a dynamic organization, a CIO is a data-evangelist and is responsible for educating everyone across the organization about accurately collecting, managing, and sharing data, internally and externally to create insights that drive daily decision-making for the entire organization.A data-driven work culture in major organizations is led by the top management and the CIOs control the rudder. 

Humanizing data for effective decisions

In order to streamline data decision-making, it becomes imperative for companies to humanize the data, which also leads to increased positive instinct and faster decision-making. To enable this, data visualization can be used to build effective connections with decision makers who need to have a thorough understanding of analytics and its ramifications. In line with this, the CIOs have been constantly chalking out strategies to train the employees and resources to work with data.

Despite there is a rise in data literacy in organizations, there should be a complete change in the organization’s mindset to enable CIOs and companies increase data-driven decision-making.The fast-paced digitalization in almost all sectors has prompted companies to shift their focus towards the importance of data and in recent years there had been a significant evolution in the digital strategy adaptability by organizations which have also considerably increased their IT budget. 

Need for data-driven culture

Another key factor CIOs are focusing on to create a data-driven culture is to analyze exactly what data they are collecting and what they want from it. They are drafting strategies to deal with clean and unbiased data coming from multiple sources and technology tools that can secure data and display it into easy-to-understand formats. In their endeavor to create data policies for different stakeholders, CIOs of major organizations are working on key areas like data profiling, stakeholder identification and education, regulations to business process mappings, API-first development practices (Application Programming Interface should be consistent and reusable), and investments into programs that promote data quality through better data tooling and pipelines.

In a nutshell, to create an effective data-driven work culture, organizations need to work closely with the CIOs to have an enterprise data catalogue combined with comprehensive data governance capabilities and provide scalable access to trustworthy data. There is also a need to develop a data-literate workforce. With the help of the CIOs, strategic decisions should be made to produce substantial commercial benefits through data-driven decision-making.

Naveen Sharma

SAP (ECC & S4 HANA), ITBP, Digital Transformation, Program Management, Pharma Serialization, Application Management, CSV, IT operation. Ex Centrient, Jubilant, Infosys, Birlasoft, Bristlecone, Essar Steel, Jindal steel

2 年

It reminds me the fundamental principle of ISO "Fact based decision making". CIO's can play vital role to support the organization in making quick & correct decision based on analytics developed through historical data.

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