Cultivating Clean, Quality Data for Trustworthy Results and Business Efficiency

As our world moves into an increasingly digital landscape, the issue of safeguarding virtual assets and critical data has never been so pressing.

The global impact of Covid-19 has emphasised an immediate need for high quality, well managed data across all sectors to create value, as well as allow businesses to continue to offer their services remotely and implement the immediate efficiency and responsiveness that is so vital in these times. 

What Is Good Data? 

Data management is a crucial aspect of business efficiency, helping organisations to stay connected with their clients and make informed decisions in regard to operations and planning. An effective data management system also allows businesses to improve the quality of their data, ensuring that the data they hold is current and can be quickly processed and analysed. Quite simply, good data is data that meets the requirements of the organisation and is what is expected. It is free of errors and inconsistencies, so it requires no time to make ready for use.

However, data that does not meet these specifications is considered bad data and can contribute to data losses, missed opportunities, security breaches and theft of both business and personnel information. Research suggests that bad data could be costing businesses more than 30% of their revenue, and around 20% of company databases contain low quality data.. Shockingly, a mere 3% of business leaders consider their organisation’s data quality acceptable. 

Bad Data is Bad for Business

In November 2020, Conservative MPs called for an official enquiry into what they believed to be ‘bad’ population data, claiming that the results of a population projection exaggerated growth predictions by 60,000 people. If the government were to act on these figures, vital natural areas such as the Forest of Arden would be needlessly considered for housing and millions of pounds would be spent on unnecessary development. Then, there’s the damage to reputation to consider, as uninformed spending and impact to our natural landscapes would inevitably lead to a very public backlash. Andy Street, chairman of the UK Statistics Authority, noted of the situation “Bad decisions – to irrevocably destroy historic countryside – are being made on the back of bad data”. 

The implications of bad data are not limited to large-scale organisations like the government. Any organisation, regardless of size or nature of business, can be negatively impacted by irrelevant, outdated, incorrect or poorly compiled data. The risks to financial resources, efficiency and productivity are high, but damage to business credibility and reputation is perhaps the hardest to shake of the lingering effects. 

Good Data Promotes Performance, Not Protection  

Although good data management will not necessarily stop deliberate hacking or phishing attempts, it can certainly help data loss due to negligence or human error. Take the healthcare sector, for example. There have been numerous global incidents of patient identification errors which can often lead to dire consequences, such as the wrong patient being operated on, incorrect medication being sent or administered and sending medical bills to the wrong patient. 

Correctly linking patient data across organisations is a key element of value-based care, patient safety, and care coordination. Duplicate or mismatched records can result in privacy risks, claim denials, redundant medical tests or procedures and reporting errors. A survey carried out by eHealth Initiative (eHI) Foundation and NextGate found that 38% of U.S. healthcare providers have incurred an adverse event in the last two years as the result of a patient matching issue. Healthcare provider and HIE executives point to data entry errors as the leading cause of their organisation’s duplicate medical records.

Despite businesses being aware that poor quality, inaccurate data wastes time and valuable expertise, creating a huge impact on profits, morale and business efficiency, many organisations first discover the pitfalls in their data during major internal events such as migration. Migration takes many forms, including systems migration, merger and acquisition migration and business change. Large-scale internal events are often the first instance of business leaders becoming aware of their data flaws – but only if the organisation is lucky enough to not have been impacted until then. Businesses should not wait for major events to prompt them to reconsider their data quality and security. 

Improving the Performance of Your Data 

There are many key data management tools and techniques that businesses can use to improve their data performance, including: 

Data Profiling: Business leaders would be wise to utilise data profiling tools to help expose any data inconsistencies and make informed, timely decisions. Data profiling can ensure that an organisation’s data is correctly structured, consistent and free from incorrect values, whilst also helping users to understand the various relationships and connections between different data sets. The process of list making is another key way for businesses to make sure that duplicate or outdated data is quickly identified and rectified as soon as possible to avoid inaccurate reporting. 

Data Catalogues: Data catalogues provide business leaders with an organised inventory of data assets using metadata to aid effective management of that information. Catalogues can help to collect, collate and organise data while allowing easy and quick access to that particular data set. When data is stored and presented in this way, businesses can better utilise their data to inform decision making, improve business processes and make effective marketing decisions and predictions. 

Data Mining: Integral business decisions and predictions can be aided further still with the use of data mining, in which large, raw data sets are transformed into insightful and actionable information. This tool works by identifying any patterns in the data so that business leaders can generate a clear picture of their customer’s behaviour. Once patterns have been identified, businesses are better able to develop targeted marketing strategies while reducing any unnecessary costs and ultimately driving sales. 

Data Lineage: Another key tool for business leaders to utilise their data effectively is with data lineage. This vastly simplifies the act of identifying and tracing errors, as data lineage records the origin of the data and tracks what happens to that data from inception to present time. This makes any anomalies in the data apparent and allows businesses to quickly rectify any data-based issues within their system, while safeguarding against that issue reoccurring again. 

Data Integration: There are many ways for business leaders to improve the efficiency and security of their data, with one such option being data integration. This combines various data formats from different sources to make the process of cleaning and restructuring data more efficient. Some organisations may also be unaware that data cleansing is another great option for ensuring data is up-to-date, standardised and free from errors. Cleansing data in this way is vital to creating accurate reports and ensures that you are conveying correct and complete information. 

Data Windows: Most businesses will be familiar with the process of analysing specific ‘windows’ of data to observe and assess business performance or customer behaviour during that time. What they may be unaware of, however, is the ability to hone in on this data further with what is known as rolling data windows. Imagine that a particular data window starts from January 1 and ends on January 7. A business would examine this window and look at how things went during that time. To implement a data window, the business would then look at days 2-8, comparing this data with the analysis made from observing days 1-7 and noting any key differences. By shifting the data in this manner, businesses can achieve a more accurate analysis of their data for predictive performance while helping to identify parameter stability. 

Using a combination of these tools and techniques can help organisations improve their results and efficiency in ways such as; 

Waste Reduction: Businesses can also improve the efficiency of operations beyond data integration by utilising data for issues such as waste reduction. By examining and extracting data insights, organisations can identify any areas of wastage or overproduction in order to streamline their practices, improve business efficiency and ultimately enhance profits. However, while data analysis is indeed a great way to review and reduce waste within an organisation, the prospect of poor data can itself create instances of waste, including wasted costs, materials and marketing efforts. Duplicate data is a key area of data inefficiency that can lead to such wasteages, like the same customer being sent multiple direct mail marketing materials and more products being manufactured than necessary. A clean, robust and ‘healthy’ database free from duplications would minimise the risk of such wasteages. 

Market Discovery and Predictions: Healthy data also allows for effective new product and market discovery, giving business leaders a window to the future and helping them to identify market trends and respond to them accordingly. Using data in this way also promotes an increase in business productivity: something that is of particular importance as The Guardian reports UK productivity slowdown is at its worst since the time of the Industrial Revolution.

While the importance of data is universally recognised, unfortunately many business leaders are simply unaware of the range of tools that are available and how to best combine them to translate data into superior performance, streamlined business operations and clear communication. How we interact with data is an ever-evolving process, but how we utilise our data to promote trust in data and business efficiency, innovation and competitiveness should be an immediate one. 

About the Author

Simon Rolph is founder of Such Sweet Thunder. He examines the challenges of poor data and discusses the tools and techniques that can support businesses to best utilise the data they have access to for increased efficiency and reduced costs.

Featured image: ©GreenButterfly