In 2016, Dell Technologies commissioned our first Digital Transformation Index (DT Index) study to assess the digital maturity of businesses around the world. Since then, we have commissioned the study every two years to monitor the digital maturity of companies.
Our third part of the DT index, launched in 2020 (the year of the pandemic), found that ‘data overload / inability to extract information from data’ was the third highest barrier to transformation, up from 11th place in 2016. This is a huge leap from the bottom to the top of the list of barriers to digital transformation.
These results highlight a curious paradox: data has the potential to become the main obstacle to business transformation. while also being their greatest asset. To learn more about the reasons for this paradox and where businesses need help most, we commissioned a study from Forrester Consulting to dig deeper.
The resulting study, based on a survey of 4,036 senior decision makers responsible for their company’s data strategy, is titled: Uncover the data challenges plaguing businesses around the world, is available for reading now.
Frankly, the study confirms our concerns: During this decade of data, data has become both a burden and a benefit for many companies, one of which depends on the company’s ability to be ready for it. the data.
While Forrester identifies several data paradoxes that hinder business today, three major contradictions stood out for me.
1. The paradox of perception
Two-thirds of those surveyed would say their business is data-driven and say “data is the lifeblood of their organization”. But only 21% say they treat data as capital and prioritize its use across the enterprise today.
Obviously, there is a disconnect here. For clarity, Forrester created an objective measure of enterprise data readiness (see figure).
The results showed that 88% of companies have yet to advance their data technology and processes and / or their data culture and skills. In fact, only 12% of companies are defined as Data Champions: companies that are actively engaged in both areas (technology / process and culture / skills).
2. The paradox “they want more than they can handle”
Research also shows that businesses need more data, but have too much data to manage right now: 70% say they’re collecting data faster than they can analyze and use it, but 67% say they constantly need more data than their current capabilities provide. .
While this is a paradox, it’s not so surprising when you consider research holistically, such as the proportion of companies that have yet to secure data defense at the corporate level. board and fall back on an IT strategy that cannot scale (i.e. bolting onto more data lakes).
The implications of this paradox are deep and far-reaching. Six in 10 businesses struggle with data silos; 64% of respondents complain that they have such a glut of data that they can’t meet security and compliance requirements, and 61% say their teams are already overwhelmed with the data they have.
3. The paradox of “seeing without doing”
As economies suffered during the pandemic, the on-demand sector has grown rapidly, sparking a new wave of data-driven businesses, anywhere that pay for what they use and don’t use. than what they need, determined by the data they generate. and analyze.
Although these companies are emerging and doing very well, they are still relatively few in number. Only 20% of companies have moved the majority of their applications and infrastructure to a model as a service, although more than 6 in 10 believe that a model as a service would allow businesses to be more agile, d ‘evolve and provide services. applications without complexity.
Making a breakthrough together
The research is sobering, but there is hope on the horizon. Companies are looking to revise their data strategies with a multi-cloud environment, moving to a data model as a service and automating data processes with machine learning.
Certainly, they have a long way to go to prime the pumps for a proliferation of data. Yet there is a way forward, by first modernizing their IT infrastructure so that they can respond to data where it is, at the edge. This involves bringing enterprise infrastructure and applications closer to where data needs to be captured, analyzed and exploited, while avoiding data sprawl, maintaining a consistent multi-cloud operating model.
Second, by optimizing data pipelines, so that data can flow freely and securely while being augmented by AI / ML; and third, by developing software to deliver the personalized, integrated experiences customers need.
The staggering volume, variety, and speed of data can seem overwhelming, but with the right technology, the right processes, and the right 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 was produced by Dell Technologies. It was not written by the editorial staff of the MIT Technology Review.