Counterintuitive as it may sound, a new study finds the latest whiz-bang technologies are giving leading companies a path to high-growth because their focus is all about people.
The top three areas of investment are in Big Data/analytics (94%), followed by IoT (75%) and machine learning (50%). These are among the major findings of The SAP Digital Transformation Executive Study, conducted in collaboration with Oxford Economics, based on feedback from over 3,000 senior executives across 17 countries and regions. The research spotlights the performance of “digital leaders” – organizations that are connecting people, things, and businesses intelligently and effectively to create change faster than the competition.
Using Tech to Act Like Small Companies
Decision-makers recognize that rethinking processes for talent management will keep them ahead of the competition. Steve Hunt, vice president of customer value at SAP SuccessFactors, sees the real transformation coming from technology that enables us to interact with each other differently. Collaborative platforms help managers easily conduct ongoing and more informed dialogues on performance calibration, while employees can quickly learn new skills from experts.
“Technology that changes how we interact with each other is the most fascinating because it’s so transformational,” said Hunt. “The technology makes it possible for large companies to have the kind of conversations they’d be having if they were a very small company. For example, if there’s an M&A on the horizon, they can quickly look across their entire talent pool to find people with that expertise and then talk about them.”
Indeed, the study findings seem to back this up. Leaders cited increasing investments in digital skills and technology as the most important revenue driver in the next two years compared to the other organizations that said it was speed to market. Seventy-one percent said that digital transformation made it easier to attract and retain talent, compared to 54% of other companies. Sixty-four percent of executives from leading companies said that their employees were more engaged thanks to digital transformation, compared to 20% of the other respondents.
Where Technology is Most Effective
The study also found that two-thirds of leading companies are making their employees’ lives easier by using technology to eliminate process roadblocks. Ninety percent of leaders expected to see value from their efforts in the next two years compared to 56% of other companies.
“Technology is most effective when it does things people aren’t good at or don’t enjoy doing, like automation or blockchain,” said Hunt. “Social learning is so popular because the best way to learn is to talk to other people. It mimics the natural way we learn, allowing people to act like people.”
Tech Changes Role of HR
The implications aren’t lost on human resource (HR) leaders who are adopting a marketing-oriented mindset.
“We’ve seen huge success in using machine learning, predictive insights, natural language processing, and all kinds of data analysis on the consumer side, and HR is waking up to the opportunities that their counterparts in marketing have benefitted from already,” said Yvette Cameron, senior vice president of strategy at SuccessFactors. “HR is asking how to use those same strategies and tactics to engage with employees. With the advent of better dashboarding and predictive capabilities, suddenly the data is starting to tell us what may happen and point us to the root cause and remediation actions we can take.”
According to Yvonne Baur, head of predictive analytics and machine learning at SAP SuccessFactors, the company is developing software tools that use machine learning in a variety of areas including predicting which employees are likely flight risks and helping recruiters write job postings to attract a larger pool of more diverse candidates. In addition, the SAP Innovation Center Network recently introduced TrueRec, a secure and trusted digital wallet that uses blockchain for storing professional and academic credentials. “We will weave machine learning into everything we do,” said Baur.