Salesforce research sees data underutilized—data skills spending is on the rise

Although most businesses continue to struggle towards rapid data adoption, the reality on the ground appears to be different. A new global survey conducted by Salesforce revealed that up to 41% of business leaders see a lack of understanding as a major barrier to unlocking the full potential of their assets. However, research shows that these same business leaders will continue to spend to strengthen data skills in the organization.

Untapped Data Research, which surveyed nearly 10,000 business leaders and decision makers from 10 different countries, highlights the need to develop relevant data tools and develop employees’ skills in using them. This would allow teams to better handle the complexity of data and access issues that prevent them from making sense of the information and creating insights from it – a barrier cited by 33% of survey respondents.

“Business leaders are experiencing one of the most challenging economic markets of our time, but they have an untapped asset for better decision-making: their data. The secret to getting true insights is to combine data with analytics,” according to Juan Perez, chief information officer at Salesforce. “A combination of data, analytics and the necessary data skills enables companies to maximize their technology investments and uncover opportunities that drive business strategy and strengthen customer trust.”

Along with the inability to understand and create insights from data, working business leaders also struggle to deal with the sheer volume of data in their stack, the survey finds. A significant 30% of respondents claimed to be overwhelmed by the volume of information within their company.

And this challenge is compounded with the amount of enterprise data set to more than double by 2026.

Significant disconnect between vision and execution

In the study, 80% of business leaders agreed that data is critical to decision-making and 73% highlighted that it helps reduce uncertainties and builds trust, but many do not seem to be using it in practice.

Only 33% of respondents said they use data to make pricing decisions in line with economic conditions, such as inflation, while 29% inform their strategy with data when launching into new markets. The responses were quite similar on the use of data to determine climate goals and diversity and inclusion policies, signaling a clear gap between vision and execution.

However, the good news is that companies are aware of all these challenges and are trying to fill the gaps by investing more in data skills. A significant 73% of business leaders said they plan to continue or increase spending on data skills development and employee training – compared to 19% who said they will reduce or make no investment in data skills.

These investments will help companies build a data culture that supports business resilience during the tough economic climate. Brad Loren, an industry analyst at Omdia, also supported the research, noting that the findings line up “pretty well” with his team’s internal studies.

Data skills in focus

According to Loren, teams need to invest in a solid foundation of non-technical skills, starting with acquiring critical thinking skills related to areas such as the scientific method, human biases, research skills/tools, and communication skills. Once this foundation is in place, they should develop it with a range of practical skills, such as learning how to work in multiple example tools (such as Microsoft Excel along with Python Pandas for data analysis).

“Business users may have an intimate understanding of a particular area of ​​expertise within the business (sales, marketing, etc.), but without these fundamental reasoning tools, they will always make invisible mistakes, such as failing to account for bias in data or a lack of buy-in to the team working on that data, which can lead to significant loss down the road,” said Lauren.

“I would recommend that companies start training users to communicate with machines through prompting (for example, to write effective messages for AI tools being created, such as ChatGPT, Bloom or Midjourney). These skills will evolve quickly over time, but an early investment in fundamental ideas like chain reasoning, which can help AI make sense of a complex request, will pay off significantly by helping business users work more effectively with these tools in the future. ,” he added.