We regularly hear that knowledge is the gas of recent enterprise, however we predict that meals offers a fair higher analogy. Once we go to fill our automobile up on the pumps, only a few of us choose a selected model– we simply desire a full tank. However in relation to what we eat, it’s not sufficient to have a full stomach; we’d like the appropriate form of meals that’s each nourishing and tastes good.
It’s the identical with knowledge. Filling up on data doesn’t essentially make a enterprise higher; in reality, the improper form of knowledge can have a extremely damaging impact on the well being of the entire organisation. That’s as a result of – within the period of the linked enterprise – the results of dangerous knowledge aren’t confined to the system wherein it resides. As a substitute, it ripples out to a spread of different enterprise purposes and processes that depend on that data.
In regards to the creator
Nick Goode, EVP Product, Sage.
Companies could not realise it, however dangerous knowledge is a severe and expensive problem. In 2016, IBM estimated that poor high quality knowledge prices over $three trillion within the US alone. (By comparability, the dimensions of the whole massive knowledge trade in the identical 12 months, in keeping with IDC, was a ‘paltry’ $136 billion.)
This will solely ever be an estimate, although, as a result of it’s tough to place a price ticket on the missed alternatives, reputational harm and misplaced income that comes from having the improper knowledge – to not point out the effort and time concerned in looking for and correcting it. Data staff spend far an excessive amount of time looking for and correcting errors of their knowledge.
Different researchers present additional proof for the devastating impression of dangerous knowledge. Gartner discovered that the common price to organisations is $15 million a 12 months, whereas a report from the Royal Mail urged that it causes a lack of six per cent of annual turnover. Why are companies failing to deal with a difficulty with such a direct impression on their backside line – particularly given at this time’s fixation on data-powered perception?
The domino impact of dangerous knowledge
You’d anticipate that the figures listed above would supply loads of meals for thought, particularly as each line of enterprise, from marketing to finance, customer service to supply chain, is now so completely dependent on accurate data on which to base their insights. Yet in our pursuit of data quantity we seem to have forgotten one of the oldest tenets of the information age: ‘Garbage In, Garbage Out’.
Too often, businesses lack a coherent data integration strategy which means that inaccurate or incomplete data causes a domino effect through the organisation.
Nothing highlights the interconnected nature of modern business better than the issue of bad data. If a department does a bad job of keeping data clean, up-to-date, and accurate, it affects every other department that relies on that data. This means that the effects are not limited to those who are responsible for managing records and updating systems; instead, they spread throughout the organisation. This results in all manner of problems: from badly-targeted marketing campaigns to poor customer service outcomes, to errors in HR and payroll, resource allocation and product development.
Another grave consequence of inaccurate data is that it can lead to people mistrusting the insights that they gain, and even resenting the data creators who have allowed erroneous information to creep into their systems.
A recipe for success
For all the hype around data-driven insights, businesses are facing a data credibility problem, with business intelligence and performance metrics badly skewed by inaccurate information. So, while no-one discounts the importance of having large data sets from which to draw insight, the more urgent challenge facing organisations is to improve the quality and accuracy of the information that they hold.
Just as the food we eat has a direct effect on our wellbeing, so the quality of their information has a bearing on the health of a business. That’s why they need to treat data as a delicacy, rather than just fuel. By focusing on data quality, they can then ensure a positive domino effect throughout the organisation, with departments and workers able to trust to the insight from analytics they derive from it.
To do this, every organisation must undertake a regular data quality audit that not only verifies the accuracy of information that is kept, but also examines the internal processes and workflows associated with gathering and storing information.
For example, the organisation needs to have complete confidence that employees are capturing all relevant information in systems such as ERP systems, and that all data is entered accurately and kept up to date. This should include cross-referencing with information held in other systems such as CRM, ensuring that the business can have faith in the data on which it bases its most important decisions.
The recipe for success is simple: be as discriminating with your data as you would towards the food you put in your mouth: prioritise data quality to ensure you get accurate insights.