The 5 Do’s and Don’ts of Business Analytics

Drive innovation with these best practices

In recent years, business analytics within the enterprise has undergone a transformative shift. Whereas this role used to be primarily a “retrospective recording function,” says Harvard Business School’s Karim Lakhani, it is now a “prospective decision-making function” at the center of organizations. To help leaders effectively place business data analytics at the center of their organizations, we’d like to offer our top do’s and don’ts.

Business Analytics best practices

In recent years, business analytics within the enterprise has undergone a transformative shift. Whereas this role used to be primarily a “retrospective recording function,” says Harvard Business School’s Karim Lakhani, it is now a “prospective decision-making function” at the center of organizations. 

“The people who are now responsible for these functions need to understand the technology and the economics and the strategy around them,” Lakhani says. “A whole range of managers now have to up-skill, retooling both their knowledge about the techniques and the strategies that go with them.”

In Teradata’s role helping enterprises get answers to their toughest strategic questions, we’ve seen what works and what doesn’t when it comes to making this strategic shift. To help leaders effectively place business data analytics at the center of their organizations, we’d like to offer our top Do’s and Don’ts for that process:

1. DON’T be led only by available data.

DO start your data exploration with the business outcome in mind. The Norwegian diplomat Christian Louis Lange famously said, “Technology is a useful servant but a dangerous master.” The same can be said for data. An all-too-common fallacy is to be led by data, limiting your analysis to what information is available. Not only does this introduce the risk of bias and blind you to potential solutions, but it can also lead you to waste time and energy on problems that don’t impact the business. And with the amount of data generated in 2020 expected to reach 44 zettabytes, the race to amass the highest volume and diversity of data simply cannot be won. Having access to a high volume and diversity of data is important, but your competitive advantage is how you use that data in service to your business questions.
 
At Teradata, this has been a helpful framework as we help enterprises achieve tangible outcomes from data. We’ve found it best to think of analytics in terms of value-adding actions that actually move the business forward.

2. DON’T restrict data access at your company.

DO democratize data and cultivate citizen data scientists at your enterprise. According to a recent survey Teradata conducted, only 25% of senior business and IT decision makers said that their business decision makers have the skills to access and use analytics intelligence without the need for data scientists. Unfortunately, even though the amount of data available has grown so rapidly, the enterprise’s ability to glean intelligence from analytics has not kept up.

One strategy for closing this skills gap is to cultivate citizen data scientists, power users who can perform both simple and moderately sophisticated analytical functions. In a recent leading analyst survey, 80% of enterprise leaders said they were investing in this role.

Citizen data scientists can only provide value, however, if they can access the right data and tools to do their jobs. We’re helping enterprises safely democratize data through Vantage Analyst, a self-service business data analytics layer that’s integrated with our Vantage platform. With Vantage Analyst, citizen data scientists can explore data with Vantage’s analytic capabilities and uncover insights.

3. DON’T think of data governance as simply a list of rules that protect your data.

DO think about how your governance fosters innovative and collaborative behavior. Your approach to data governance is vital, particularly as you open up access at your enterprise. But your data governance must do more than just ensure integrity and security — it must be developed as part of your broader business data analytics management strategy.

According to MIT Sloan Management Review, data governance plays a key role in fostering innovation. Sam Ransbotham and David Kiron write that “To be most effective, data governance needs to be embedded in an organization’s culture.” They add that “data governance needs to be more than a system of tactics to derive business value — it must actually influence organizational behavior.” Keep in mind the people behind the processes and policies you’re developing, and design governance structures that encourage participation and discourage siloes.

4. DON’T just use data to validate current ways of thinking and working.

DO use business analytics to create new processes, products, services, and entire business models. Ransbotham and Kiron write that more and more companies are using data to “innovate not only existing operations but also new processes, products, services, and entire business models.” Leverage artificial intelligence and machine learning to augment human ingenuity, automating more data processing and freeing up your people’s time to think creatively about your business challenges and growth opportunities.

In our current “digitization of everything” era, the more people at work innovating at your organization, the more business value you’ll uncover. Your business analytics team has a central role to play in that process. Equip your analysts with the data and tools they need to glean intelligence about the past, present, and future of the enterprise.

Curious about how Teradata Vantage can help you democratize business analytics effectively?