Quality data proves critical to business performance

75% of businesses who improved data quality in 2021 exceeded annual objectives, but data quality and skills shortage leave 56% of businesses still not able to capitalise on data.

New research from Experian reveals that better data management and data quality has helped businesses to navigate the Covid-19 pandemic, bringing them closer to customers.

The annual Global Data Management report, which surveyed 905 data practitioners and data-driven business leaders worldwide, found the majority (75%) of businesses who have improved their data quality in the last year have exceeded their annual objectives in some way.

This includes objectives relating to customer experience, managing talent and workforce development, data security, and improving business resilience. Meeting these objectives will ultimately help these organisations reach their revenue growth targets.

Recognising data as a critical asset to build business resilience, most businesses (89%) say that contact data is key to customer engagement, indicating its use in building a recovery plan. Similarly, 88% suggest data management has allowed them to keep up with understanding their customers’ rapidly changing needs that continue to be impacted by the pandemic.

2022 data priorities

Almost every business respondent (97%) said they plan to make their data management programme more flexible and agile over the next 12 months.

Improving customer experience is a top priority (52%), with businesses eager to use data to enable more customer centricity though better operational efficiency (48%) and better customer experience for customers offline and online (44%), for example.

However, inherent barriers are hampering businesses from maximising on data usage, such as a lack of data skills and a decline in data accuracy. Over three quarters (77%) say that inaccurate data hurt their ability to respond to market changes during the pandemic, while39% say poor quality data has negative effects on customer experience. Meanwhile, 84% think a lack of data skills in the business hampers agility and flexibility in their organisations.

Andrew Abraham, Global Managing Director, Data Quality, at Experian, comments: “The last year has tested every industry, with a new requirement for business models to be agile and change in line with their customers’ rapidly shifting demands. Our research shows that businesses who have improved their data quality were not just better equipped for this but exceeded their performance expectations too.

“However, business experiences with data accuracy and issues around how data is managed remain and are unlikely to improve unless businesses upskill current employees and continue to work with wider industry and government on addressing the data skills gap.”

Delivering a data boost

The Global Data Management report highlights how businesses can seek to overcome challenges as a result of data management and data quality limitations.

Investing in talent – evidence shows a lack of data skills affecting data management. As well as investing in employee training, previous Experian research found more could be done to attract graduates into data roles. Most students polled (67%) said they wanted companies to do more to promote data roles, and over half (53%) said they were considering a career in data. With a data literate workforce, a business is armed with talent that can make timely, data-driven decisions.

Clean up your data – the report reveals that only 44% say that their CRM/ERP data is clean, and that they can fully leverage it (against 50% suggesting this in 2020). By enriching your data, organisations can open up new information about customers while also making sure your existing data is accurate. When you purchase a data set from a trusted source, you can be sure the data regularly refreshes to keep your data lists updated and reliable.

Prioritising your insights – 72% say they have so much data in their organisation that it is difficult to prioritise where data management can add most value. DataOps for example, can shorten development cycles, increase deployment frequency, and create more dependable releases of data pipelines, in close alignment with business objectives. This practice helps organisations adapt more quickly to changing conditions and prioritise data effectively.