Investing in data can pay substantial dividends. It can drive customer-centricity, boost operational efficiency and even develop brand-new data products and business models. Many industries recognize this enormous potential, which is reflected in an increased investment in data and analytics in 2023, despite uncertain economic times.
Here are the top five challenges data leaders face in improving their return of investment in data.
1. Low business impact from data initiatives leads to increased pressure to reduce technology costs and limited capacity for innovation.
While most companies agree that data should be at the heart of everything they do, the majority have not defined the outcome they want to achieve. In fact, a survey showed that less than one third of CDOs measure the value achieved by analytics or AI projects. This lack of well-defined criteria in measuring success diminishes the CDOs’ capacity to draw a clear business case for funding and implementation. In the context of ever-increasing demand and need for impact, CDOs need to set a bold vision on business value, communicate this business value to the executive management team and align a strategy to deliver it.
2. Data initiatives often do not incorporate organizational change considerations, which can result in lagging ethical use of data and future non-compliance of artificial intelligence regulations.
Most companies already have ample data to make insightful decisions, but most of that information is poorly managed and exploited. According to a study made by Carruthers and Jackson, “40% of data leaders report their organization has little or no data governance framework.” This has led to an exponential increase in inconsistent and unreliable data – lacking structure and standards in data processing. Besides improving data quality, organizations must manage security and compliance concerns. This is necessary to comply with the increasing legal requirements (such as the European AI act or ESG regulations) and avoid the business risks associated with poor governance. CDOs need to involve the legal, security and compliance teams at the start of the process and design a data model and governance that scales.
3. Current talent shortages mean enterprises must upskill existing employees.
Poor data literacy and staff shortages are commonly cited as roadblocks to data and analytics programs’ success, hitting best-in-class companies and laggards equally hard. In fact, about two-thirds of data leaders believe that most employees in their organizations are currently not data literate. Data analytics leaders must produce new strategies to compensate for this trend, such as internal recruitment, upskilling and appropriate partner models. Improving data literacy goes hand in-hand with data evangelization, which is key at every level of the business. It promotes employee empowerment at the individual contribution level, and it also facilitates top-level buy-in of data initiatives.
4. The role of the CDO is misunderstood or not provided with the necessary authority to create a company-wide data culture.
Organizations are shifting the focus from tools and technologies to the human side of transformation so they can become a fully data-driven business. They realize that one of the main roadblocks to success is a culture challenge that makes it hard for employees to accept change. Data leaders play a key role as orchestrators and facilitators of this change. If the role of the CDO is not well understood, then they may lack the authority they need to execute their responsibilities or business stakeholder involvement and support. Organizations need to overcome this gap by clearly defining and formalizing data roles and responsibilities. Businesses need to understand how data supports their work and data professionals need to understand the business context of their work. A company-wide culture is crucial to drive the journey toward becoming a data-driven organization.
5. Both business and IT teams need guidance on what tools are best for their needs and their environment.
New, innovative technologies are being introduced to the market rapidly while most companies are dealing with aging analytics platforms and infrastructure and the excessive cost of operating on-premises systems. There is also a lack of direction on the technology platform and tools/vendors in terms of whether they will be open source, cloud-based, etc. Inefficient service design makes it difficult to scale properly. The key to finding the right partner is to find the leading analytics provider that best fits your value requirements.
Data leaders that overcome these five challenges will be able to turn data into a source of competitive advantage. ISG helps companies become data-driven organizations. Contact us to find out how we can help.