Poor Data Quality - Increases Risk of Business Failure
This post discusses the need for businesses to make data quality a board room discussion and should be part of the business strategy. Data is what underpins the value of any digital or technological investment and the need to get the correct high quality data is critical - getting it wrong has shown to have a diametrical opposite effect, increasing costs and resulting in wrong decision making with fatal consequences.
In addition data quality has shown to be a key link to successful digital adoption and improved efficacy. This post concludes by emphasising the importance of creating a objective risk framework that focuses on developing better benchmarks for data quality.
What is Data Quality?
On a basic level, Poor quality data is not fit for purpose, is inaccurate, incomplete, or out of date data . Poor quality data increases risk and can cost you time and money. It also falls short of GDPR rules this highlights the far reaching consequences in a business of poor quality data.
75% of businesses waste an average of 14% of revenue on bad data quality which equates to £197.788m every year!
From a technical perspective, poor quality data slows down the entire data architecture, caused by poorly structured data in any storage space such as cloud, warehouse or lake infrastructure. Duplication of data can mean increased storage capacity and cause systems to have errors. Data not having correct values is also one of the key reasons AI or Automation technology do not deliver correct results. The long tail effect is bad experiences by staff members and customers - having negative impact on retention and growth.
Data Quality Improves ROI in technology
The growing investment by businesses in technology and digital transformation is great news for the economy and businesses alike. We are happy to be part of that journey but with a certain amount of anxiety.
We have observed, there is boardroom pressure from investors to ensure there is return of investment from the technology. With the added pressure of limited time for C-level executives to deliver a technological solution. Add to the mix of making sure the smooth transitions to quicker digital adoption by the internal team and customers. With the ultimate goal of delivering increased efficacy of service and operations. A key factor to meet these demands by Chief Technology Officer ("CTO") and Chief Data Officers ("CDO's") is being able to benchmark the correct and quality of data.
81% of those surveyed said they’ve found it difficult to generate meaningful business intelligence.
The pandemic has kicked started a digital revolution and increased the stakes for businesses, in June 2021, City AM reported that over 65% of UK companies planned to increase their spend on new technologies – with 54% of businesses suggesting the adoption of technologies helped them successfully overcome the challenges presented by the COVID-19 pandemic. For 62% of businesses, meanwhile, investment into new technologies was anticipated by June 2022 at the latest.
The investment in digital technologies has the potential to increase the UK’s GDP by 7%, equating to an additional £232 billion boost to the economy by 2040. To make this potential economic growth a reality, there needs to be a shift in boardroom thinking. One such factor is the way risk is assessed when it comes to delivering a transformation project. Top of the board room agenda should be the data quality which should take equal priority when considering annual technology budgets and the overall business strategy.
The Cost of Bad Data Quality
The indirect costs to poor quality data can be harder to measure. This is because it isn't immediately apparent the true cost of poor data quality. It may be a longer-term consequence, such as a damaged reputation. Although digital infrastructure realise on data, so poor data quality can weaken evidence, create mistrust, and lead to poor decision-making.
Data quality is a major issue for UK plc.
Although 99% of businesses have a data quality strategy, many fully admit to still having problems with their data, with 86% thinking their data might be inaccurate in some way.
It is recognised reputation is one of the key pillars of any business success story, and Poor quality data also poses a reputational risk. Just the GDPR issues, with data quality being a requirement of GDPR. Duplicated data could result in contacting the same person multiple times. This can lead to feelings of frustration and mistrust, as well as wasted time and resources.
Over 70% of those who run loyalty programmes say they they’ve suffered problems through having inaccurate customer information (34%) and not having enough information about their customers (24%).
When it came to inaccurate email addresses, 67% reported problems with email deliverability - 28% said customer service had suffered as a result of poor email hygiene and 26% said that had been unable to communicate with customers due to inaccurate information.
Incorrect or missing personal information could also have significant impact on the individual. For example, they could miss important deadlines or not receive necessary information. Unreliable and contradictory data can make it difficult to know what is correct. Users may then question the accuracy of your data, and this may create mistrust towards your organisation.
44% of those surveyed said that incomplete, missing data is the most common problem for them and 41% said that it’s outdated data that is their biggest issue. Key drivers for having clean and quality data include business efficiency (62%), customer satisfaction (54%), cost savings (44%) and customer profiling (43%).
Data that is poor quality may also lead to you missing vital opportunities, or cause failures in service provision. For example, inaccurate or out of date data may result in an unnecessary service provision in one area, whereas high quality data could outline more valuable opportunities.
Poor data quality can also lead to organisations being unable to assess their own effectiveness and whether money and resources are used in the best way possible. High quality data can lead to more targeted organisational strategy, better spend of public money and increased operational effectiveness.
Despite this the research does conclude that data quality is moving up the corporate agenda and will be key to the success of the crucial projects UK businesses will carry out this year, including digital transformation, big data and analytics. Businesses are quite rightly realising that the era of quantity over quality data is over. Organisations are becoming more aware of the value that consumer data can bring and the costs that poor data can have on the bottom line.
Digital Bucket Company:
The Digital Bucket Company specialises in data solutions, providing small and large businesses with end to end solutions. To find out more about our approach to data risk and managing data quality please contact us by emailing email@example.com