Almost half of companies are working to improve data quality and processing in the next two years, according to a MIT Technology Review Insights report released Thursday. Forty-three percent of companies are increasing the adoption of cloud platforms and boosting data analytics as part of an enterprisewide strategy.
Enterprise leaders seek cloud-native platforms to support their data goals with 63% of respondents using cloud services or infrastructure widely in their data architecture, according to the report. MIT Technology Review, in a partnership with Databricks, surveyed 351 global senior data officers for the report.
Investing in cloud infrastructure underpins enterprisewide scalability of data strategy, according to the report. For one-third of respondents, cloud-native architecture is the most critical advantage of their ideal new architecture over the existing one.
Of data strategy "high-achievers" interviewed for the report, 74% run half or more of their data services or infrastructure in a cloud environment. High achievers account for just 13% of respondents excelling at delivering on their data strategy.
For organizations looking to meet data goals, it starts with baby steps.
"Unless the business is ready to leverage the tools, has the maturity to extract the insights, and processes and logic are agreed upon, we're only adding to the spaghetti architecture," Sol Rashidi, chief analytics officer at The Estée Lauder Companies, said in an interview for the report.
Understanding where data fits is part of mastering the basics companies must complete before advancing modernization and emerging technology projects. Companies can't "skip crawling and walking with ML and go straight to running," Rashidi said.
Instead, leaders should select use cases that align with business objectives and start slowly, according to Don Vu, chief data officer at Northwestern Mutual, in the report. Business user input along the way helps deploy the right use cases into production.
Businesses have been able to align their data efforts with broader company strategy, as chief data officers provide integration support, according to Vu. As cloud becomes a C-suite priority, it's become easier for tech leaders to make their case.
Yet, there will still be hiccups along the way even if the data use case is perfectly aligned to business strategy. Only 12% of respondents to the MIT Technology Review survey say they have achieved optimal price/performance for their analytics workloads.
“Unless a use case shows big wins in sales or efficiency gains, you will always have a big ROI challenge," Naveen Jayaraman, VP of data, CRM & Analytics at L’Oréal, said in the report.
Four in ten (39%) companies successful at AI deployment ran financial analysis on risk factors or conducted an ROI analysis, according to Gartner data. Leaders can try demonstrating value quickly to overcome the ROI hurdle.
"The quicker you can demonstrate value from ML and data science, the quicker you get users’ buy-in and build management confidence in the value of both to the organization," said Patrick Baginski, senior director data science at McDonald’s.