Out in front with ERP and business analytics

Today’s leading companies are capitalizing on data and analytics to gain a significant edge. Is yours one of them? What can you do to catch up?

With data-driven technologies, such as IoT, AI and Blockchain, becoming more prevalent, analytics offers companies an abundance of opportunities to use their data strategically. The challenge for many companies, however, is how to go from one-off and ad hoc activities to a long-term, strategic transformation that places analytics at the core of its operations.

According to a survey by McKinsey, companies with the greatest overall growth in revenue and earnings receive a significant portion of that boost from data and analytics. How are these companies managing to capitalize on data and analytics? The survey indicates their leaders are creating both data and analytics strategies for the long haul. They are also creating a strong data-driven culture by making data a core part of employees’ workflows. Meanwhile, they are also ensuring that high-quality data and modern technological foundations are in place to support these efforts at scale.

A thoughtful strategy

Among respondents whose companies have not yet met their data and analytics objectives, many report the lack of a strategy for these areas as a significant obstacle to success. Of those that have met their objectives, 21% rank having a strategy as their number-one key to success. The high performers also understand the value of implementing a formal strategy that aligns activities among data, analytics, and the business: 60% say these strategies are mostly or completely aligned, compared with just 44% at other companies.

A powerful data culture

Creating a data culture means instilling a set of practices that brings together data talent, tools, and decision making so that data become the core pillars of company operations. According to the survey, high-performing companies are ahead of their peers in adopting and implementing data-culture best practices, such as having employees consistently use data as a basis for their decision making. They are also much more likely to report having a data leader in the C-suite, making data and self-service tools accessible to frontline employees, and creating an organizational culture that supports rapid iteration and tolerates failure.

Modern supporting technology

At Pipol, we’ve experienced how important a company’s underlying technology is to its data and analytics efforts. A growing number of our customers are upgrading or seeking solutions to support their analytics strategies. The survey backs this up, reporting that high-performing companies are much more likely than their peers to have deployed a modern data architecture. In fact, data architecture is the second-highest ranked challenge (after strategy) to reaching a company’s data and analytics goals.

The importance of data quality

A robust data architecture allows organizations to support the rapid collection and sharing of data that enables frontline employees to access and use the data they need. It also helps establish and maintain the high levels of data quality required to support effective data-based decision making. The survey bears out the importance of data quality in driving analytics adoption. Respondents report better data quality than their peers at other companies, and across respondents, low data quality was the factor most often cited as the biggest obstacle to getting employees to use data consistently for decision making.

Want to talk about your analytics strategy with us? We offer a Business Intelligence Assessment for data-ambitious businesses and can help you determine your next steps. Get in touch.