When it comes to adopting a data strategy, Canadian companies are concerned about cost, limited time and lack of understanding. This helps explain why only one in five executives has put in place a game plan for “big data” and why just one in four is very, or somewhat, likely to do so in the future.
Given the recent advances in data analytics technology, these findings point to a limited recognition of the true value that data can deliver, and what impact it can have on the bottom line.
Businesses are already awash in mountains of information, not only from traditional data sources, but from new technologies such as social media and real-time customer feedback. Failure to tame these data dooms companies to making decisions based on “gut feel” rather than proven metrics.
But properly analyzed data can deliver insight into a wide range of key performance indicators. By shining a light on a company’s strengths and weaknesses, data analytics can help improve brand management and customer satisfaction, reduce third-party risk, enhance procurement practices, and even detect – and prevent – fraud and corruption.
Realizing these benefits, however, requires a new approach to differentiate between the “noise” and the data that are truly valuable. There are four key issues:
Technology: Given the challenges of system integration among many organizations, it’s no wonder executives fear the costs associated with big data initiatives. But it is not always necessary to invest in new systems and tools. It is about making better use of existing technologies. By blending old-world business intelligence with new-world big data, a company can pull only the information needed for effective decision making.
Data: Companies often think only of transactional or financial data, customer data or website statistics. The truth, however, is much broader. Data analytics can provide insight into the metrics most likely to affect corporate performance – from products, services and marketing programs to financial plans, supply chains, transactions and employees.
People: Before a big data program can work, companies need to identify the people within the organization who can most benefit from specific analytical insights and provide them with the training they need to use that data effectively.
Culture: Moving from gut-feel decision making to a data-driven mindset often requires a cultural shift. But as a work force becomes more analytical, it will be easier to identify and resolve business challenges.
As many companies have discovered to their detriment, rushing into a big data project – particularly a pure IT-led one without key performance metrics or indicators – can be a losing proposition. However, ignoring data analytics poses an equivalent threat: Missed opportunities. To avoid getting lost in the sheer volume of data created, received and accessed daily, companies need to adopt a road map to address their competitive needs, systems requirements, cultural changes and an effective governance structure. This enables an organization to reap the benefits.
Dominic Jaar is the national leader of KPMG’s information management services practice.
Follow us on Twitter: