October 26th, 2021 – A new survey from DataIQ, in association with Mango Solutions, one of the UK’s largest data science consultancies, has revealed that incremental value equivalent to 18% of business revenues may be generated as a direct result of an advanced data science approach. Even organisations at the early stages of data maturity claimed a 4.1 percent revenue increase directly attributable to data science.
The study was conducted by DataIQ and surveyed 103 data practitioners and analysts ranging from heads of department to chief data officers and global directors.
The study found that a total average of 6.7 percent of business revenue is generated via data science. This almost trebles to 17.9 percent of annual revenue within organisations with an advanced level of data maturity. So, whether a business practices data science – with data-driven processes and analytical modelling embedded in decision-making – or whether it has yet to leave the planning stage, data science is highly likely to yield a significant return.
Data science, which applies advanced analytic methods (such as machine learning and statistical modelling) to business challenges, is incorporated into the company vision of a third of data mature organisations, according to the survey.
It also found that commitment at C-suite level has a direct correlation on the data maturity of an organisation, with more than four out of five (83.3 percent) data science functions created through board initiatives within advanced-level organisations. These kinds of businesses are twice as likely (50 percent) than the average business (24.1 percent) to communicate the impact of data science directly through their chief executive.
These same organisations are found to be pulling ahead in the data science race. Two thirds (66 percent) of organisations with advanced levels of data maturity introduced their data science function three to five years ago, while 50 percent of organisations surveyed in the early stages of development have yet to launch a single data science function.
The survey also highlights the importance of measuring data science initiatives. Two thirds (66 percent) of organisations with advanced data maturity are able to define relevant metrics to establish the impact on the business of each data science initiative. This compares to only half (50 percent) of early-stage companies, the other half of whom are failing to measure the impact of any data science initiatives at all.
Richard Pugh, co-founder and chief data scientist at Mango Solutions, said: “Data is driving digital transformation across industries, and the application of data science is having a transformative impact. However, many companies are still not yet applying data science to their business. These organisations are really in danger of being left behind in an increasingly-digital world, as data makes their competitors more intelligent, efficient and engaging. It’s fantastic to see that even those with emerging data science capabilities are managing to generate significant value from their investment. Beyond that, the benefit of maturing a data science capability and aligning it with business objectives is clear, delivering a 4-fold increase in expected value, compared to those with emerging data science capabilities. While this all aligns with anecdotal evidence, it is great to get some real data to support the potential and impact of data science investment”.
A copy of the report, can be downloaded here: https://info.mango-solutions.com/delivering-value-through-data-science
About Mango Solutions www.mango-solutions.com
Mango Solutions, an Ascent company, is one of the largest data consultancies of its kind in the UK. It uses data science to solve real-world business challenges. For more than 19 years, it has enabled leading businesses to revolutionise their data science capabilities, boost productivity and maximise profit margins. Its culture of curiosity, continuous learning and embracing challenges provides the perfect environment to nurture and inspire each generation of data scientists and data engineers to keep pushing the boundaries of data-driven transformation.
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