High-quality data and its full understanding across an enterprise is increasingly crucial to ensure decision-making is free from bias and driving innovation in the digital economy
Data is no longer an issue confined to the IT team. Its quality, trust and understanding within an organisation is paramount in decision-making. The real value of information is not in its technical nature or how it supports applications, but rather how knowledge workers within the business can comprehend and leverage it in new ways.
Truly understanding data means thinking about the environment it lives in. Businesses need to know what systems are involved and how the data is manipulated on its path between applications, data lakes and reports. It also increasingly requires knowledge of third-party data sources.
“When you ask people if their data quality is good, they’ll almost certainly say no,” notes Rex Ahlstrom, chief strategy and technology officer at BackOffice Associates, which provides solutions for improving data quality across the enterprise. “The narrow way people used to look at data has really expanded into a multi-dimensional problem of trying to get a better handle on the trust and understanding of data.”
Data quality has been an issue facing companies for many years. Previously, if data was unclean or inaccurate, the whole process broke down and required manual intervention. With the emergence of analytics and machine-intelligence tools, however, data quality has become even more crucial because, if the data is biased, it will lead to bad decisions.
When utilised successfully, data-driven decision-making can help grow revenues and serve other core business objectives. Its value may be as simple, yet effective, as improving internal processes to boost efficiency and minimise the cost of execution.
But a robotic process automation tool making automated decisions about supply or inventory tools, for example, could prove to be very costly if it has been fed poor or incomplete data. Biases in the data itself can seriously hinder business decision-making.
As companies are increasingly influenced by automated methods of decision-making, it’s vital to ensure the data flowing into systems is not only complete, but can also be backed up for compliance purposes when reports are delivered to governing bodies.
The narrow way people used to look at data has really expanded into a multi-dimensional problem of trying to get a better handle on the trust and understanding of data
“The challenge becomes much more sophisticated,” says Frank Schuler, BackOffice Associates’ vice president SAP technical architecture. “Knowing the underlying data is good quality keeps companies out of court and reduces compliance failures, as well as optimising processes, reducing costs and driving innovation. Data could look perfectly fine, but is driving biased decisions so data quality becomes enormously more important.”
Enterprises need policies and rules that ensure data is managed in an effective way, and staff can see how it flows across the organisation and impacts decision-making. Only a complete understanding of where the data came from, how it changed on its journey and its current state can enable them to comprehend all its source and lineage.
Often companies don’t understand what can be archived or decommissioned and the impact of doing so across the enterprise. By cataloguing all their systems, BackOffice Associates provides companies with a Google-like experience of searching and immediately discerning how data is being distributed throughout the organisation.
“Few companies know all the potential locations where their data resides,” says Mr Ahlstrom. “There are so many applications, on-premise and in the cloud, structured and non-structured, that it becomes very hard to quantify. Cataloguing those environments enables everybody to understand what lives within the applications.”
There are many tools focused on only one thing, such as analysing data quality, but companies need to empower their knowledge workers to contribute to understanding data. The challenge is getting line-of-business leaders to care about data quality.
“You have to orchestrate the processes by which they participate and provide ways to become data contributors in an effort to crowdsource the improvement of information at the enterprise level; that orchestration of resources is crucial,” says Mr Ahlstrom. “BackOffice Associates creates new user experiences that transform a logical or physical understanding of data into a business-level understanding of information.”
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