Data is the key to overcoming the ‘new digital divide’

“‘It’s very clear that in this environment, which is changing at unprecedented and unexpected levels, that agility and the productive use of data has become more important than ever,’ said Svenja Falk, managing director at Accenture Research
Supheakmungkol Sarin, head of data and AI ecosystems at the World Economic Forum, identified four ways companies can tap into data’s value: to establish new revenue streams; to underpin new ecosystem-enabled business models; to deliver richer experiences for customers, users, suppliers, shareholders, and partners; and to drive real-time insights and make better decisions.
‘It’s about democratization — getting data out to the broader organization, understanding what data means, what data we need, what data we don’t know we need yet, and experimentation,’ said Peggy Gulick, director of digital transformation operations at manufacturing company Kohler Co. ‘It’s all about how you get to that next level of using data to truly be innovative and drive advancement.’”

Why digital optimization is the new digital transformation

“The key to a successful digital strategy is understanding what keeps your customers coming back, and then optimizing and personalizing digital experiences based on those insights.
Many companies still focus the majority of their efforts on acquiring new customers, which is important for short-term growth, but long-term, sustainable growth requires lifelong customers and brand advocates. When you gain better insight into how your customers engage with your digital products and experiences, you can dramatically improve offerings to increase retention and, ultimately, revenue.
Digital transformation must be rooted in cross-functional alignment, particularly when it comes to managing and dispensing data.
Data provides much more value to the company if all teams not only can access it, but utilize it to experiment with new ideas and innovate new solutions that customers actually want.”

“Sophisticated companies are making good progress connecting internal and external data to create functional insights that can be easily shared and used by decision makers across the business. But two key developments have brought a certain urgency to the question for businesses across the globe.
The first is the pivotal nature of this moment for business. Consumer habits and behaviors continue to be shaken up, and longstanding business and operating models disrupted. And with that, we’ve discovered that the ability to use data intelligently to sense and respond to changing market conditions and patterns of consumer behavior has never been more important.
The second key development is the rapid advances in real-time data and analytics technologies, specifically artificial intelligence (AI) and machine learning. It means that, rather than simply analyzing what has happened in the past, companies now have the ability to spot new and evolving patterns in the moment.
Effective personalization relies on having a cloud-based architecture able to collect and process real-time data to deliver the right contextualized messaging at the right moment through the right channel.”

“It’s now clear that decision-making AI and machines will be the primary driver of economic growth over the next decade in what’s being referred to as the ‘Machine Economy.’
Not only will the Machine Economy depend on data to operate, but all these smart applications, machines, and connected devices will continue generating exponentially increasing amounts of data. The last decade was a fierce data arms race, and that will be even more true in the Machine Economy as data continues to rapidly increase in both volume and value.
According to McKinsey Global Institute, data-empowered organizations were not only 23 times more likely to acquire customers, they were also 6.5 times more likely to retain customers, and 18.8 times more likely to be profitable.”

“With more than 25% of businesses dealing with between 1,000 and 9,999 data sources, integrating, reconciling and managing this data to get to its value has also become exponentially more challenging.
A recent survey of global Chief Data Officers (CDOs) by IDC indicates that high levels of data fragmentation are forcing 37% of data leaders to spend most of their time grappling with data complexity rather than driving business transformation.
Conversely, organizations with mature data management generate up to 250% more business value from their data than companies with less data maturity.”