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Survey of leading financial institutions reveals disconnect between digital transformation progress and data readiness
CAMBRIDGE, Mass., May 27, 2020 /PRNewswire/ -- Despite universal advanced or expert data management expertise in large U.S. financial institutions, more than a third (thirty-five percent) that are pursuing digital transformations with less-than-anticipated impact are not expecting results for three to five years. Further, nearly half of survey respondents say they can't keep up with competitors nor service customers in an optimal way, according to a new survey from Tamr, the data mastering company, on the state of data and digital transformation.
Tamr conducted the survey of 300 C-suite executives in United States financial institutions with revenue of $1 billion or greater.
Sixty-nine percent of those surveyed agreed that data is very important to digital transformation efforts. Further, fifty-eight percent of those engaged in a digital transformation initiative believe leveraging data is vital to the future success of the business. Yet, further questions from the survey reveal unresolved challenges with data and its readiness. This is surprising given the importance of digital transformation to financial organizations and level of investment in it over the past fifteen years.
Key findings from the survey include:
Desire and willingness to invest in digital transformation is near universal
- Only one percent of those surveyed are not pursuing digital transformation.
- The main drivers of digital transformation are keeping up with/staying ahead of competitors (cited by forty-seven percent) and moving faster than competitors (cited by forty-five percent).
Data and data management are drags on digital transformation
- Sixty-three percent of those that report that their data is insufficiently supporting their efforts say it's because their data is too vast to analyze.
- In fact, twenty-eight percent identify unreliable data as a motivator for digital transformation, with sixteen percent describing their data as disorganized (nine percent) or unusable (seven percent). This despite the fact that ninety-three percent of respondents report having either advanced or expert data management expertise.
There are notable impediments to managing data
- Common obstacles include: Data volume (fifty-one percent), data management methods unaligned with digital transformation initiatives (forty-four percent), outdated data management methods (forty percent), data variety problems (thirty-six percent) and data velocity problems (twenty-nine percent).
What's missing
To better contribute to the success of their digital transformations, respondents agreed that their data must be in the following state:
- Accurate, complete and credible (sixty-four percent)
- Enables clear insights into informed decision-making across the business (sixty-four percent)
- Accessible and brought together from key systems (sixty-one percent)
- The primary driver in making us a data-driven organization (fifty-eight percent)
Weaknesses cited
- Seventy-five percent can't keep up with constant data changes over time.
- Fifty-five percent of those reporting non-scalable data management practices say they are choking on too much data.
- Among weaknesses, fifty-four percent cite speed to insight, forty-seven percent having to unify hundreds - even thousands - of data sources across the enterprise, and thirty-nine percent labor-intensive processes for data wrangling.
- Only two percent reported no areas of data management practice as needing the most improvement toward digital transformation initiatives.
A strong desire for solutions to data volume, variety and velocity
- More than half of respondents involved in digital transformation initiatives (fifty-two percent) say they are ready to purchase a solution to assist with data volume, variety and velocity because more than half (fifty-four percent) have solutions that don't scale or provide a complete, accurate view of data.
- In addition, fifty-three percent say that they aren't utilizing their current data to its full potential because it's siloed throughout the organization; fifty-one percent report needing help with the constantly changing state of their data; and forty-six percent say their digital transformations are slow and not delivering the impact they should.
"Our survey found that financial institutions are spending too much time trying to integrate company data (at forty-two percent), too much budget on cleaning company data (forty-one percent) and too much time trying to unify company data (thirty-nine percent)," said Jenn McAuliffe, Head of Sales, Tamr. "In spite of all this, only three percent already have a viable solution in place. This perhaps suggests a fast-mover advantage opportunity for those who implement the right solutions now."
About this Survey
This survey was conducted by Tamr in conjunction with Censuswide, who surveyed 300 C-level executives and founders from financial service companies within the United States with revenue of $1billion or greater. Fieldwork was carried out between November 6 and November 20, 2019. Censuswide abided by and employs members of the Market Research Society. All survey panellists are double-opted-in (with an opt-in and validation process) in line with MRS and ESOMAR standards.
Additional Resources:
About Tamr, Inc.
Tamr is the leading data mastering company that accelerates data-driven business outcomes for large organizations. Industry leaders like Toyota, Societe Generale, and Thomson Reuters trust Tamr to manage their enterprise data as an asset. Tamr's unique approach of using human-guided machine learning algorithms to accelerate data mastering projects lets the world's largest organizations enhance their data operations, rapidly activate latent data, and increase the velocity of business outcomes through data-driven insights. With a co-founding team led by Andy Palmer (founding CEO of Vertica) and Mike Stonebraker (Turing Award winner) and backed by investors including NEA and Google Ventures, Tamr is transforming how companies get value from their data.
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SOURCE Tamr, Inc.
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