When bad, inaccurate or untimely data can bring your world crashing down, Doug Munn, Head of Elektron Real Time, looks at how to prevent disaster through the use of quality data.
With so much pressure on every decision and so little time to make it, it’s essential to have absolute trust in your data.
Data is like the rails on which you base your train of decisions; all it takes is one small flaw, and the whole process can be derailed. Then you’re faced with rescuing whatever you can from the train wreck.
I don’t want to paint too negative a picture, but the impact could be considerable.
There’s the cost of the initial deal based on bad data, and the associated expense of mitigating subsequent bad trades. IBM estimates the annual cost of poor quality data at US$3.1 trillion in the United States alone.
There’s also the risk of falling foul of MIFID and other regulations, with the collateral damage to your organization’s reputation, and employee and client confidence.
Poor decision-making risks
Research by Roberts Wesleyan College, New York estimates that every adult makes 35,000 remotely conscious decisions every day.
That’s just one individual, deciding what to do next in their personal and work life. Some of those decisions, such as “which shoes shall I wear today?” or “what shall I have for lunch?” may seem relatively trivial.
But consider the gravity of that person’s decisions at work. If they’re employed in the financial markets and making a critical trade, the consequences of that decision going wrong could be immense.
From wiping millions of dollars off share values to crippling a company’s reputation, poor decisions can have immediate impact and painful long-term consequences.
Listen to podcast — The Number Crunch – How can you ensure quality and reliability of your data?
Good decision-making benefits
In its article The Decision-Driven Organization, Harvard Business Review said “a company’s value is no more (and no less) than the sum of the decisions it makes and executes”.
Its survey of executives from 760 global companies revealed the companies most effective at decision making and execution generated average total shareholder returns nearly six percentage points higher than those of other firms.
The importance of data quality
So we’ve seen the effect of good and bad decision-making.
Yet every decision relies completely on the veracity of the data used to make that decision. With good, accurate and timely data, it’s still possible to make a good or bad decision.
But with bad, inaccurate or untimely data, the resulting decision can only be a bad one. Data quality and reliability are the most critical factors in determining the success of every decision.
What, then, determines data quality? It needs to be:
- Accurate – meeting the standards and rules for its particular data field.
- Consistent – those standards of accuracy are always delivered.
- Accessible – the data is presented in a meaningful, easily interpreted way.
- Complete – with valid values and not blanks or defaults that might leave you guessing.
- Timely – the very latest real-time data, so you’re not misled by old, possibly irrelevant information.
- Reliable – delivered as quickly as you expect, every time, so you can always rely on it.
Not just what you know, but how you use it
To those characteristics, we could also add a seventh criteria: convenience.
Although that may not seem directly connected with quality, data is ultimately only valuable if it’s compatible with the platform and app you use.
This enables you to take full advantage of it whenever and wherever you need, adding another dimension to the data’s quality and value.
Watch video — Can you trust the quality and reliability of your data?
How then do we ensure we only ever deal with quality, reliable data?
The answer is to use a source that not only supplies the most comprehensive, pertinent, up-to-the-second data, but also runs its own comprehensive quality checks to verify its provenance and accuracy.
To give you confidence in the data, those quality checks need to be frequent and applied throughout all phases of the data life cycle, from content source and collection to distribution.
Be a data superhero
You would expect such a data source to be widely respected and extensively used, with a broad customer base that includes many blue-chip names.
The most successful trades and decisions are always the result of good quality, reliable data. To be a data superhero, keep demanding quality and don’t settle for anything less.
Thomson Reuters has been providing customers with reliable, objective and unbiased information for over 150 years.
Today, Thomson Reuters Elektron Data Platform delivers quality, reliable data managed by over 4,700 content experts in 17 languages.
Each day, Thomson Reuters runs tens of thousands of quality checks to ensure accuracy throughout the content collection and distribution process. These checks are constantly reviewed and updated by a team of 50 data scientists worldwide.