Salesforce survey sees data trove untapped — data skills spend to rise

Even as most enterprises continue to race toward rapid data adoption, the reality on the ground appears to be different. A new global survey conducted by Salesforce has revealed that as many as 41% of business leaders see lack of understanding as a major barrier to unlocking the full potential of their data assets. However, the survey suggests these same business leaders will continue to spend to boost data skills in the organization.

The Untapped Data Research survey, which involved nearly 10,000 business leaders and decision-makers from 10 different countries, highlights the need to deploy relevant data tools and develop employees’ skills to use them. This would enable teams to better handle data complexity and access issues that keep them from understanding the information and generating insights from it — a barrier mentioned by 33% of the survey respondents.

“Business leaders are experiencing one of the toughest economic markets of our time, but they have an untapped advantage for better decision-making: their data. The secret to driving true insights is marrying 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 generate insights from data, business leaders working are also finding it hard to deal with the sheer volume of data in their stack, the survey finds. A significant 30% of the respondents claimed that they are overwhelmed by the amount of information within their company. 

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

Major disconnect between vision and execution

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

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

However, the good news is companies do realize all these challenges and are looking to fill the gaps by investing more in data skills. A significant 73% of the business leaders said they are planning to continue or increase spending on data skills development and training for employees — against 19% who said they will decrease or make zero investment in data skills.

These investments will help companies establish a data culture that supports business resilience during the tough economic climate. Brad Loren, an industry analyst at Omdia, also backed the survey, noting that the findings align “quite well” with his group’s internal studies. 

Data skills in focus

According to Loren, teams should invest in a solid foundation of non-technical skills, beginning with the acquisition of critical reasoning skills relating to areas such as the scientific method, human biases, research skills/tools and communication skills. Once this foundation is ready, they should build on top of it with a number of pragmatic skills such as learning how to work within multiple tooling paradigms (such as Microsoft Excel together with Python Pandas for data analysis).

“Business users may have a tight grasp of a given area of expertise within the business (sales, marketing, etc.), but without these foundational reasoning tools, they will invariably make invisible mistakes such as failing to account for bias within the data or a lack of inclusiveness within the team working on that data, which can lead to significant loss down the road,” Loren said.

“I would recommend that companies begin training users to communicate with machines through prompting (for example, writing effective prompts for generative AI tools such as ChatGPT, Bloom or Midjourney). These skills will rapidly evolve over time, but an early investment in foundational ideas such as chain reasoning, which can help step the AI through the logic of a complex request, will pay significant dividends by helping business users work more effectively with these tools going forward,” he added.