The world of data has never been more intriguing to work in. Data was assigned to a back-office task twenty years ago. It is the foundation of an organization’s competitive advantage in 2023. The necessity for IT leaders to pay close attention to their data, AI, and analytics estate has increased as a result of digitization.
Technology executives will see data play an increasingly important part in their career evolutions in novel and fascinating ways, beyond the necessity to achieve firms’ ambitions to improve customer experiences and streamline operations: By the end of the next year, 25% of traditional major enterprise CIOs will be held accountable for the operational outcomes of the digital business, thus taking on the role of COO by proxy.
Technology and data leaders must evaluate the good, bad, and ugly of the rapidly changing data landscape if they are to prosper.
The good news is that the data organization has become a value organization.
The fantastic news is this: 83% of businesses claim to have tasked an executive with leading their data strategy. This is an increase of almost 700% in just ten years (just 12% of businesses had chief data officers in 2012). (CDOs). 70% of these data executives report to the company’s president, CEO, COO, or CIO, which enables them to concentrate on tasks that provide value to the business rather than those that have the appearance of being cost centers.
Technology CEOs are also increasingly organizing their teams to help with the creation of data products. Harvard Business Review claims that this can save the time needed to incorporate data in new use cases by as much as 90%, lower total ownership costs by as much as 30%, and lessen the burden of risk management and data governance.
In order to ensure that members of a data product team don’t merely produce algorithms but instead work together to deploy full business-critical apps, over 40% of data leaders report adopting a product management mindset to their data strategy and recruiting data product managers.
The bad: Data leaders are misunderstood
Only 40% of businesses reported that the CDO job is now successful within their organization, despite the fact that 92% of businesses claim to be receiving returns on their data and AI investments.
Data CEOs seem pretty down, too: 62% said they believe their position is not well understood. They highlight the typical problems of newly formed organizations, such as unrealistic expectations, hazy charters, and difficulty in influencing.
Everyone involved usually finds this frustrating: According to MIT, just half of Fortune 1000 businesses’ data executives can use data to promote innovation, and 25% state that there is no single point of authority for data within their organizations.
The outcome: Over 75% of businesses have failed to transform into data-driven businesses.
This shows that data executives must build their companies in a way that immediately and visibly adds value to their employers.
The ugly
The average term of data leaders is less than 950 days, which is even worse. This contrasts with the usual CEO’s tenure of 7 years and the normal CIO’s tenure of little over 4.5 years.
Everyone loses when data executives don’t have the time to build the framework their organization needs to succeed with data. Best practices are lost, data scientists, engineers, and analysts lose their credibility, and business partners lose faith in the leadership’s capacity to create the data-driven organization they have promised to.
Now what?
In spite of the potential impending macroeconomic crisis, current study indicates that more than two in three data leaders (68%) intend to expand data management spending in 2023.
Our internal analysis demonstrates that CDOs and CIOs have typically handled budgets of $90 million, with roughly 50% going to employees, 40% to third-party software, and 10% to corporate overhead costs.
It will be fascinating to watch how they choose to handle their investments this year. According to a recent study, 52% of data leaders will prioritize enhancing control over data and processes, followed by culture and literacy (46%), and acquiring a comprehensive understanding of customers (45%).
Along with changing away from centralized data teams building data pipelines and static dashboards in favor of a data mesh model, data executives must also modify the organizational structure of their teams. The development of dynamic data products and applications takes place here, where data practitioners sit within the business domains and own their own data.
By bringing data and analytics projects closer to the line of business, the data mesh approach helps business users see a real return on their investment. In the next five years, about 60% of survey participants said they intend to switch to a data mesh architecture. The data product manager, the program manager, the UX leader, and the data engineer are the minimum of four crucial roles that CDOs should rely on to construct this new paradigm.
While some of these positions have been around for a long, the career of data product manager is fresh and untapped for aspirant data professionals.
Three modifications that must be made right away
Data leaders will need to make the following three significant technological changes:
- Shifting from data warehouses to data lakehouses to eliminate time-consuming and expensive data migration and cost-effectively accommodate the increasing volume, variety, and velocity of data.
- Making the switch from isolated business intelligence dashboards to data products that are enterprise-grade (globally available, highly dependable, and designed for huge data volume) and can withstand scenarios that are of a consumer-grade nature (fast and responsive, optimized for high concurrency and work in real-time, all the time).
- Increasing emphasis on operationalizing AI and real-time. An organization’s data and analytics infrastructure must be optimized for real-time choices in order to deliver great customer experiences. Regrettably, there is simply too much data and input for data teams to be able to give users the help they require. The most recent CDO survey found that 55% of businesses manage 1,000 or more sources of data. The main obstacle to digital transformation is data fragmentation and complexity. To deploy intelligent services on top of their unified data platform, leaders will need to figure out how to create a center of expertise.
To sum up, enterprise leaders have made large investments in data and analytics since it’s becoming more and more crucial to enterprises. Enterprise data executives, however, should adjust to their organizational structure, the strategies they are pursuing, and the types of technologies they are buying to produce measurable and tangible business value in order to maximize ROI.
