Modern analytics strategies have the potential to uncover new revenue streams, improve the quality of products and services and cultivate closer engagement with profitable customers. But to fully capitalize on this potential, enterprises must balance a complex mix of technical, organizational and cultural requirements. With this complexity come possible roadblocks that can hinder efforts to gain competitive advantage and also dilute returns on investments.
Fortunately, the experiences of analytics leaders shed light on the most likely roadblocks so organizations with evolving analytics projects can head them off early. Here are the four challenges most frequently faced by global enterprises and how you can overcome each one.
Poor Collaboration Among Key Stakeholders. Teamwork among a cross-section of departments is essential for evaluating, championing and implementing analytics-driven initiatives. It’s especially important to foster close collaboration between two areas—lines of business and IT. When these groups are in sync, people can outline their key objectives for IT personnel, who in turn can act as expert advisors who explain what analytics innovations are available to support the business.
This helps explain why, according to research from Forbes Insights and Cisco, 70% of leaders say a successful analytics strategy hinges on close collaboration between IT and business units. A solid majority of leaders—58%—describe their company’s business/IT collaboration as “excellent.” Other enterprises, however, struggle with these relationships. Only 15% of global executives, overall, rate analytics interactions between these two groups as “excellent,” while 39% rate business-IT collaboration as “fair”.
The consequences of this can be significant: 57% say poor collaboration creates risks that investments in analytics won't give people the information they need, while more than a third consider this shortfall a deterrent to capitalizing on technology innovation.
Action item: Create a cross-functional analytics team that includes stakeholders in technology, business, operations, legal and HR to promote the use of analytics in individual departments as well as across the enterprise.
Succumbing to the Allure of the Latest and Greatest Technology. The hottest buzzwords in IT today come from the realm of analytics—artificial intelligence, machine learning and predictive analytics. Many enterprises are turning this buzz into budget commitments. In fact, 40% of global organizations plan to invest in AI in 2018. This, and the other variations of intelligent software, have the potential to generate valuable business insights and automate actions based on the results. But without clear goals for how to best use this information, companies risk spending large sums and seeing small returns.
Action item: Don’t implement advanced technology for its own sake. Carefully evaluate the factors that are driving your business today, and identify areas where the application of intelligent analytics software will improve business outcomes. Consider whether new technologies will help your organization become more productive, save money or lead to the development of better products and services. Much of the data that enterprises gather is just noise—until the right technologies and techniques are applied to understand what it means.
Relying Too Heavily on Either Top-Down or Bottom-Up Initiatives. C-suite commitment is vital for creating data-driven businesses, but top-down mandates alone won’t ensure that analytics become widely used for decision making. Senior-level imperatives must be combined with bottom-up, grassroots projects designed to weave traditional and advanced analytics into the fabric of how organizations work. To do this, wise personnel management is crucial.
Action item: Honestly assess the prevailing analytics expertise of your current staff. Doing so can offer two important insights. First, it will help you identify analytics-savvy influencers within your organization—people who may not have the most senior positions, but, because of their expertise and interpersonal relationships, can sway peers to adopt new ways of working. Second, the internal assessment will also uncover talent gaps that need to be filled. Opt for new hires or outside partners who demonstrate a solid track record in using data effectively.
Failing to Build on Success. Many enterprises have pockets of analytics maturity, where an individual department has acted unilaterally to harvest insights from the data it collects. Finance, marketing and IT have traditionally been at the forefront of efforts like these. These early adopters are valuable resources for leaders wanting to use data to drive decision making throughout their companies.
Action item: The corporate analytics team should identify business initiatives where data-driven decision-making already delivers clearly documented benefits. Use these positive results to promote the wider adoption of analytics techniques in the enterprise and to justify investments in advanced tools, such as AI. Interesting and successful projects happening in some departments will help motivate other work groups to adopt analytics.
Potential roadblocks abound for enterprises striving to expand their use of analytics for competitive advantage. But by addressing these challenges head-on, you can set your organization up for success.
To learn more, read, “Advanced Analytics: The Key to Becoming a Data-Driven Enterprise.”
