Ready for takeoff?
Eight barriers blocking the runway
Businesses know they should extract value from their data. But many organizations find it difficult to overcome barriers and sector-specific issues. There is a clear reward know the reward businesses who are able to extract maximum value from their data. Our research shows that companies that successfully use data are already outperforming their peers by as much as 20%.
Nevertheless, many organizations are frustrated with the limited progress they have made so far. They are confronted by these barriers that threaten to prevent them reaching the destinations they know are possible.
Analytics is the means for extracting value from this data by generating useful insights. Without analytics, businesses have no way of using their big data to establish competitive advantage.
- The unknown destinations. Many companies understand that they possess valuable and useful data, but do not have a clear idea of what questions to ask of their data.
- The underlying technology challenges. Many organizations lack the means to cope with the sheer scale of data flowing into the business. They can be intimidated by ideas such as real-time analytics, and do not know which technological tools can help them with their concerns.
- The lack of a holistic approach. Too often, businesses approach big data on a project-by-project basis, and with distinct silos within the business. Some businesses are now creating specialist roles, but these are not recognized enough at the C-suite level.
- The shortage of talent. Businesses need data scientists, visualization experts, business intelligence analysts, data warehousing professionals and data privacy experts. Developing these skills inhouse is difficult in the short term, but buying them in externally is expensive and simply not possible in many markets.
- The fear of cyber attack. As your business’ dependence on data and analytics increases, so does your vulnerability to cyber attack, and the level of impact and damage that breaches will cause. This includes regulatory risk as well as outright business and reputation loss.
- The difficulty of building the business case. While executives may accept the argument for big data initiatives in general, they want to understand the potential of specific projects before signing off on any related investments. Yet with relatively few such projects completed, it is difficult to provide such information.
- The need for legal and regulatory compliance. Many organizations understand that data privacy and security will have an enormous impact on their work in big data and analytics. But if they do not address the regulatory and legal risks, it can cost them a lot of money, and their reputation.
- The need for customer data. Customers appear to be less willing to share data with companies, for the fear that their data is being misused and their privacy violated. Companies must address how to use the data they have to better serve customers.