The establishment of data-driven culture has been an important topic of discussion among enterprises. To obtain transformational returns on their investments, many digital leaders and enterprises are investing heavily in data analytics, especially in the post-pandemic world.
But how can enterprises move ahead into full gear to effectively implement data-driven culture? The solution lies in following a comprehensive data-driven road map to obtain the desired business objectives.
Making The Data-Driven Shift: Where to Start
Becoming data-driven is not just about making tactical decisions around IT infrastructure. That’s because optimizing IT infrastructure alone won’t make an enterprise more successful. It necessitates a shift in mindset and efforts from employees and management. Orchestrating data analytics needs executive support, data proficiency, and a reliable community to ensure the objectives, mission, and needs of the whole enterprise are met—in technology and process.
That’s why CIOs should assess these questions to understand whether their enterprise is ready to act, contemplate, and behave differently with business data:
- What is our enterprise’s data strategy, and if it’s indeterminate, what challenges exist where business data might help?
- What data skills do workers have? Are there gaps in data capabilities among professionals?
- Do we have a reliable in-house community that will commit to help enterprises in leveraging data analytics methodologies? If not, how can we form it?
- What practices need to be polished to ensure better data governance?
- Is there an understanding among internal members that what data is stored and secured by the enterprise?
Analyzing these questions and problems can be easier said than done. It often puts CIOs and digital leaders at crossroads: whether to board on the journey of data-driven to stay competitive or continue with their traditional data management approaches. If CIOs opt for becoming data-driven through data analytics implementation, they have to follow a comprehensive road map, which is discussed in the next section.
Comprehensive Roadmap for CIOs to Form a Data-Driven Enterprise
Determining Processing Powerhouse
Successful data processing needs the involvement of a project manager and system administrator to handle technical tasks, and analysts to work with data tools. CIOs should ensure that all these people work toward the objective of delivering superior service to their clients and case teams.
Similarly, one of the most important things that CIOs should consider when establishing an internal processing protocol is choosing the right powerhouse for handling enterprise data. Without a system in place, it is easy for the workforce to become disorganized and lose or misplace data, resulting in serious legal consequences. Apache Hadoop stands as the leading processing powerhouse in the domain of enterprise data analytics. With this tool, the workforce can cluster multiple sources and analyze huge datasets in parallel more rapidly.
Establishing Modern Data Architecture
Despite the exceptional enhancements in data and technology over the past decade, several enterprises are still failing to benefit from their data. As per a recent survey, around 87% of digital leaders and business users have difficulty retrieving enterprise data and insights. Fragmented data results in disordered insights. Hence, CIOs should ensure that business users should not have to devote hours on curative data preparation tasks and upholding insubstantial data pipelines.
Establishing a centralized Cloud data infrastructure is an affordable way for CIOs to combine multiple data sources, and then add best-of-Cloud intuitive tech solutions to form a modern data stack. Opting for Cloud data infrastructure enables the workforce to maintain scalability and data governance and keep their business data structured, as it allows users to make room for improvements.
A reliable data infrastructure should also be convenient for both data leaders and frontline workers. To achieve this, CIOs should augment their data infrastructure with AI tools. This helps frontline workers to perform searches via live query so that no time-intensive data aggregations or movements are required to derive insights.
Let’s look at a popular business case of AI-augmented data infrastructure:
The leading multinational company ‘Panasonic’ dealt with a lack of data transparency across its supply chain, severely impacting demand forecasting accuracy and workforce efficiency. As the management stated, the implementation of an AI-powered data infrastructure helped their employees obtain better visibility of comprehensive supply chain data and forecast their demands and market needs.
Digital leaders of Panasonic stated that “With AI data infrastructure, our supply chain professionals could predict demand on a daily basis instead of monthly, all while enhancing accuracy.”
Some other outcomes experienced by Panasonic include:
- Abridged analytical silos and organized data management
- Upskilled their employees to adopt a data-driven culture and rely on facts to make tactical decisions
- Utilized data-driven insights to improve customer experience
Prioritizing Self-Service Analytics
For anyone to competently evaluate data in their profession, they must be data-proficient. It’s not just obtaining the appropriate skills, but also the interest in making data-driven conclusions rather than following instinct or gut feeling analysis. Therefore, CIOs should hire people with the right aptitude and skills to make data-driven decisions and help enterprises adopt successful data culture through show-and-tell training, sessions, and other undertakings.
An enterprise that regularly supports and encourages self-service analytics will experience better complacency. Self-service analytics also play a crucial role in data culture empowerment. Organizations embracing self-service analytics can enable better collaboration and enhance productivity.
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Combining Data Enthusiasts to Increase Analytics Usage
CIOs should create a network of people within their company who use business data to analyze, share and collaborate. A robust community will thrive if CIOs help set up the time, space, and resources for every worker in an organization to grow their data skills. Eventually, this will create data-driven culture and learning as more workers realize the power of insights identified individually or as a group. Furthermore, enterprises can reduce data silos, modernize processes, and better align industry metrics.
Closing Thoughts
Having a digital leader like CIO is essential, who connects workers, documents resources, and redeems analytics across the enterprise. On the whole, CIOs can make an organization data-driven by keeping business data analytics at the core. In-house data communities, as stimulated by the Chief Information Officers, can also flourish by linking with external groups who share similar passions for business data.
