Issue link: https://read.uberflip.com/i/1472353
7 On the other hand, according to the survey, most "maintainer" and "survivor" organizations remain farther behind when it comes to data strategy goals: they're more likely to have a data strategy with gaps in execution that prevent them from getting the most value out of their data, are in earlier stages of data strategy implementation, or don't yet have a data strategy at all. The pandemic, says Vachhrajani, has highlighted those gaps and brought data-driven challenges to the forefront. "Many companies still have mountains of technical debt, with old-guard databases and technology that they have failed to modernize," he explains. Data strategy priorities As organizations plan for the year ahead, most recognize that implementing a strong data strategy, supported by the right cloud, analytics, and AI-driven technology is key. By far, the biggest priority for survey respondents is to boost technology investments, including in machine learning and AI. In fact, 45% of all respondents say investing in technology is their number-one priority (see Figure 5). For respondents in the "thriver" group, that number soared even higher: more than half (57%) say technology investment is their top priority as they continue to mature their data strategies. That's true for Aquiline, which has made technology investment and implementation a core exercise. "We spent a lot of the last 18 months either ripping out and replacing legacy systems or putting systems in place where they didn't previously exist," says Lutz. "Then we worked to make sure the data from those systems was of high quality and certified." The company worked diligently to make data output a "golden source of trustworthy data, readily available to the people who need it," he explains. Another top priority for companies at every stage of the data strategy journey is hiring and training employees in necessary data-focused skills. A full third of thriver respondents consider finding and retaining the right talent to be a top priority. Some companies are ready to train those with the right soft skills: "We're looking for curious people who are able to learn independently in order to solve issues and deeply understand business needs," says Graindorge. "But it's also about training. You need people who can adapt to their environment, who you can train and give the right tools, and then offer them space to practice, fall, and succeed." Overall, companies that have thrived over the past year have leadership backing significant investments in people and technology to build a data strategy that succeeds, says Vachhrajani. "They invest in building skills across the whole company, not just in technology or data functions, and they also invest in adopting technology like cloud at scale across the entire company." Successful, tech-forward organizations also realize that every product and application will soon be infused with machine learning, Vachhrajani explains, so they're not only investing in machine learning and AI but reskilling and hiring employees who can help deploy the technology at scale. "It's all about working to identify how machine learning can help them solve problems better in every area of their business," he says. 79% 79% 79% " People forget that data inputs are often messy and require time to clean and maintain. Mikael Graindorge, Senior Manager, Commercial Analytics and Insight, Thermo Fisher MIT Technology Review Insights