What We Learn About Data Quality From Sherlock Holmes
“Data! Data! Data! I can’t make bricks without clay.”
Sir Arthur Conan Doyle understood the importance of logic when it comes to solving a mystery. In The Adventure of the Copper Beeches, his character, Sherlock Holmes, becomes frustrated at a lack of detail that makes his decision-making process impossible.
In effect, Holmes requires concrete facts to solve the mystery presented by Miss Hunter’s job offer from Mr Rucastle.
Holmes’ exclamation is one of the best-known lines that Conan Doyle ever wrote, and that may be because of its wide-ranging appeal. In the modern world, the need for accuracy is as relevant as it was in the author’s era. Businesses must locate good quality information to make effective decisions, and for precisely the same reasons as Sherlock Holmes.
Detecting Data Quality Problems
In order to move a business forward, its management team must analyse its current position (financial, strategic etc), and use that analysis as the basis of a plan. Accurate, timely data forms the basis of many critical decisions.
When a business does not have good quality data, it will inevitably speculate and guess.
Bad data clearly results in poor quality decision-making, and bad data is responsible for wasting resource at every stage. Employees, faced with bad data, instinctively ask the IT department for assistance. IT then spends a disproportionate amount of time coordinating a rescue effort and handling the related administration. In the meantime, critical business processes flounder.
Meanwhile, various members of staff are forced to come up with new ways of working to get around the data quality problem. They might feel that they have to cherry pick data, take educated guesses and using non-standard analysis that hasn’t been vetted by the business as a whole.
The end result is a dataset that is inconsistent from department to department. Each part of the business will have manipulated the data for its own means, so no single part of it can be trusted. Some departments abandon their analysis completely and begin to work without any guidance at all.
Bricks Without Clay
On the DQ Global® blog, we often talk about consequences to business when data quality is poor. If you do not have clay – reliable information – you cannot make the bricks that will form the structure for future growth.
There are also many undesirable consequences for your customers, including:
- Delays to queries or problem resolution
- Inefficient service from customer facing staff
- Poor continuity from one customer touch point to another
- Problems interpreting customer behaviour
- Difficulties getting hold of customers
- Inability to track staff interactions if there is a complaint
- Inability to protect customer data
In essence, this all impacts on productivity and profit in the long term.
Data Quality Solutions
“Crime is common. Logic is rare. Therefore it is upon the logic rather than upon the crime that you should dwell.”
When a data quality problem occurs, the best course of action is to deal with it logically, rather than apportioning blame. Forget the past and work towards healthier data. The sooner the business starts its data quality initiative, the sooner its shareholders, customers and employees will see positive results.
Sherlock Holmes was known for his logical approach to problem solving, and the same can be true of your business. No matter how far the data has decayed, DQ Global offers a data quality software solution that will allow you to work with facts – not guesses. Like Holmes, you can make bricks with clay – and give your business the solid foundation it needs to build on its success.
