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In 2016, Dell Technologies commissioned our first Digital Transformation Index (DT Index) study to assess the digital maturity of businesses worldwide. Since then, we have commissioned a biennial study to monitor the digital maturity of businesses.

Our third installment DT DirectoryLaunched in 2020 (pandemic year), it found “data overload/lack of insights from data” to be the third highest barrier to transformation, ranking 11th in 2016. This is a huge leap from the bottom. approaching the top of the list of obstacles to digital transformation.

These findings point to an interesting paradox: data has the potential to be businesses’ number one barrier to transformation. same time are their greatest assets. To learn more about why this paradox exists and where businesses need help most, we launched a study with Forrester Consulting to dig deeper.

The resulting research, based on a survey of 4,036 senior decision makers responsible for their companies’ data strategy, is under the title: Uncovering Data Challenges Impacting Businesses Worldwide, now available for reading.

Frankly, the study confirms our concerns: In this decade of data, data has become both a burden and an advantage for many businesses – it depends on how data ready the business can be.

While Forrester identified several data paradoxes hindering businesses today, three major contradictions stood out for me.

1. The paradox of perception

Two-thirds of respondents say their business is data-driven and say that “data is the lifeblood of their organizations.” But only 21% say they look at data as capital and prioritize use across the business today.

It is clear that there is a disconnect here. For some clarity, Forrester has created an objective measure of businesses’ data readiness (see figure).

Results showed that 88% of businesses have yet to develop their data technology and processes and/or data cultures and skills. In fact, only 12% of businesses identify as Data Champions: companies that are actively involved in both areas (technology/process and culture/skills).

2. The paradox of “don’t want more than they can start”

The research also shows that businesses need more data, but have a lot of data to process right now: 70% say they collect data faster than they can analyze and use, but 67% say they consistently need more data than their current capabilities provide . .

While this is a paradox, when you take the research holistically, for example, it’s an IT strategy that has not yet secured and scaled data advocacy at the Board level (i.e. bolting to more data lakes).

The implications of this paradox are deep and far-reaching. Six in 10 businesses struggle with data silos; 64% of survey respondents complain that they have too much data so they can’t meet their security and compliance requirements, and 61% say their teams are overwhelmed by the data they already have.

3. The “seeing without doing” paradox

While economies have suffered during the pandemic, the on-demand sector has expanded rapidly, fueling a new wave of data first, data everywhere, paying for the data they use and using only what they need, determined by the data they produce. and analyze.

Although these businesses are emerging and doing very well, their numbers are still relatively small. Although more than 6 in 10 believe the model-as-a-service will enable companies to be more agile, scalable and provisioned, only 20% of enterprises have migrated most of their applications and infrastructure to a model-as-a-service. uncomplicated applications.

make a breakthrough together

The research is sober, but there is hope on the horizon. Businesses want to rethink their data strategy with a multi-cloud environment by moving to a data-as-a-service model and automating data processes with machine learning.

Of course, it has a lot to do to prepare the pumps for data proliferation. Still, there is a way forward by first modernizing their IT infrastructure so they can meet data at the edge where they live. This includes maintaining a consistent multicloud operating model, preventing data sprawl, while bringing enterprises’ infrastructure and applications closer to where data needs to be captured, analyzed and acted upon.

Second, by optimizing data pipelines, so data can flow freely and securely while enriched with AI/ML; and third, by developing software to deliver the personalized, integrated experiences that customers crave.

The staggering volume, variety, and speed of data may seem overwhelming, but with the right technology, processes, and culture, businesses can tame the data beast, innovate with it, and create new value.

To learn more about the study, visit www.delltechnologies.com/dataparadox.

This content is produced by Dell Technologies. It was not written by the editorial staff of MIT Technology Review.