Assess your company's analytics readiness and learn how to reap the rewards of data analytics

While leaders understand that analytics is important, it can be difficult to grasp how different business units and individual departments utilize data and analytics and how that ultimately affects business performance. Image: Shutterstock

Each day, we produce roughly 2.5 quintillion bytes of data, and that number will only increase. Without analytics, data is virtually useless. That’s why the ability to make sense of the deluge of incoming information is essential to business success.  It provides the insights at speeds that enable companies to be more effective, efficient, and responsive to their customers.  Most organizations understand this – and many have begun their data analytics journey – but few feel they are utilizing data and analytics to full effect to drive their business success. In fact, a large majority of senior leaders are not satisfied with the outcomes delivered through analytics.

The returns from data analytics have been well documented, but why are so many companies not realizing the promised benefits?  That’s what led us to think through and introduce the concept of “analytics readiness” – the degree to which companies effectively collect and utilize data to guide business decisions. Through that process, we learned that many companies try to achieve analytics readiness by hiring more data engineers or data analysts. But that’s only one part of the solution – and maybe not the most critical component. Through our research with companies across the globe, we identified seven dimensions of analytics capabilities that are critical to analytics readiness: culture, leadership commitment, operations and structure, skills and competencies, analytics strategy alignment, proactive market orientation, and employee empowerment. We found that each of these seven dimensions can play a key role in achieving analytics success.

Assessing Analytics Readiness

After surveying over 300 senior executives across B2B organizations on their analytics capabilities, we found that companies fall into one of three categories:

• Laggards – Those who have barely begun their data analytics journey
• Strivers – Those who are making efforts but still not reaping the full benefits of analytics
• Leaders – Those who have reached the “promised land” of data analytics proficiency

We then created a diagnostic tool, – that can be found below  – to help companies: (1) discover where they currently are on the road to becoming proficient with data and analytics; (2) assess where their strengths and weaknesses lie; and (3) understand what areas they need to focus on and the steps they need to take to reach the “promised land” of data analytics leadership.

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While leaders understand that analytics is important, it can be difficult to grasp how different business units and individual departments utilize data and analytics and how that ultimately affects business performance.  That is why we recommend that the diagnostic tool be completed in a small group workshop setting composed of a range of employees from different departments within the organization including executives, managers, customer-service employees, stakeholders, and even suppliers.

The results of the assessment will reveal the company’s strengths and weaknesses when it comes to analytics readiness, help to prioritize action steps, investments, and the allocation of resources, provide benchmarks for gauging progress, and, ultimately, enable the company to become more data-driven and competitive. The process of completing the tool can also aid in creating a common language and mindset surrounding data analytics, which will help create alignment and traction across the organization.  

Getting to the Promised Land

Once there is consensus in the workshop around analytics capabilities, company leaders can then determine the best course of action to reach the next level in their journey. No matter the current status of a company, there is always room for improvement or intentional maintenance. In each of the seven dimensions, there are specific things a company can do to improve. From our research, we created a playbook that lays out specific action steps that companies can take to improve their performance on each of the seven dimensions.  Here is a sample of potential action steps:

Culture – Establish an analytics centric culture by integrating data analytics into daily workflows and including all employees in discussions and processes around analytics.

Leadership Commitment – Leaders can demonstrate commitment to analytics by taking ownership of data analytics and incorporating it into rewards, compensation, and recognition. Be transparent about data analytics strengths and weaknesses as well as processes.

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Operations and Structure – Create data and analytics consistency throughout the organization and show how non-technical employees can utilize and access data. Never compromise security, privacy, and compliance.

Skills and Competencies – Hire talent with data analytics skills and train existing talent to be proficient in data and analytics.

Analytics Strategy Alignment – Ensure your analytics strategy complements, aligns with, and influences the company’s overall competitive strategy. There should also be alignment throughout the different departments within the organization.

Proactive Market Orientation – Use data analytics to predict customer preferences and accelerate innovation. Analytics should provide valuable insights that can increase profits and improve customer satisfaction.

Employee Empowerment – The proof is in the pudding of business performance. Show employees the returns from data analytics and demonstrate how data analytics can be used in their daily tasks to make an impact on their role and deliver desired company outcomes.

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Regardless of where a company is on their analytics journey – laggard, striver, or leader – working through these dimensions can help leaders discover and address areas of weakness and enhance areas of strength so they can continue to move to the next level of analytics readiness.

Senior leaders don’t have to be data and analytics experts, but they do need to be able to have informed conversations with data engineers and analysts and understand what the company needs to move forward on its analytics journey. Data is only going to grow as will the need for analytics. It is critical that leaders are well versed in this area and prepared to develop the right culture and mindset.

[This article has been reproduced with permission from Knowledge Network, the online thought leadership platform for Thunderbird School of Global Management https://thunderbird.asu.edu/knowledge-network/]