Building a Data Analytics Culture Takes Time
Everybody wants to become a data-driven enterprise, and if you read many corporate statements or annual reports, it appears they’re already there. However, simply decreeing that things are to be data driven isn’t enough.
There’s a lot of work that needs to be done at the back end, and even more work at the front end. A recent report from PwC states that organizations may be overconfident about their abilities to deliver data insights. “Many organizations are confident that they have the capability to extract value from their information for commercial and operational advantage. Our analysis shows, however, that this confidence is largely misplaced. Close scrutiny of interviews conducted with 1,800 senior business leaders shows that very few are able to mine information to its full potential, and fewer still can make the most of the benefits that accumulate as a result.”
Organizations “lack the required skills, technical capabilities and culture to truly gain the greatest advantage from their information,” the PwC report’s authors contend, looking at data from 1,650 businesses. “Most businesses in our survey are failing to adapt to the new information dynamic, particularly in terms of the more sophisticated data analytics tools, software and reporting mechanisms – with Excel the dominant tool to extract value from information deployed by the majority.”
Data integration is a challenge for most organizations. A survey from Ventana Research, 62 percent struggle with accessing and integrating data in efforts to deliver predictive analytics. “Although technology for these tasks has improved, complexity of the data has increased through the emergence of different data types, large-scale data and cloud-based data sources,” says Tony Cosentino, analyst with Ventana Research.
The PwC report’s authors provide advice on becoming a data-savvy organization:
Provide clarity on roles, responsibilities and harness appropriate skills and tools. “Big data and analytics are often the domain of a dedicated function – usually part of IT – that has built up skills and resources around centers of excellence,” the PwC report states. “However, this siloed approach is sometimes out of step with the business. Even better is to assemble a cross-functional team at the start, which can explore the issue from a variety of angles and quickly iterate.”
Focus, focus, focus. Organizations seeing data-driven advantage need to adopt a “relentless focus on identifying and understanding the interdependencies between risk and value together with assessing how business governance, organizational capabilities, technology and the evolving role of data analytics can be effective enablers,” says PwC.
Don’t sweat the small stuff. “Every organization’s priorities are likely to change from time to time. Your information and analytics priorities will reflect this.”
Use what you’ve got. “Wherever possible, embed information management responsibilities within existing structures rather than building new ones. These resources are best drawn from your business and will comprise IT, business knowledge and data skills.”
Don’t create unnecessary bureaucracy. “Data governance needs to be understood and made relevant to everyone in the organization. It needs to be something that is easy to work with.”
Understand that not all data is equal. “Work on what matters. It is also important to clearly define how robust data needs to be. You will need to think the same way when you build your analytics too – focus on analytics that will drive decision making.”
Create the right behaviors. “Data producers need to know what is expected of them and this needs to be set by data consumers. Where required, these expectations should be agreed, formalized and performance monitored as part of a formal personal performance management process.”
Build in data analytics from the beginning. “If you design and improve your business processes to recognize the data that they create and the analytics that they consume, you are far more likely to succeed in improving the quality of the end product, the information that you use to manage the business.”
Secure executive sponsorship. Good governance includes “clear sponsorship from the leadership and with this we are seeing an emergence of the role of the Chief Data Officer.”