Corporate investments in data analytics are booming, right along with the explosion in data generated by many enterprises. The global market for data analytics platforms and tools reached $200 billion in 2019 and is expected to hit $274 billion by 2022, according to IDC. Yet many organisations are not seeing the returns they expect from those investments. The promise of modern analytics, aided by advances in machine learning, is to improve decision-making in support of critical business objectives, from growing the customer base to retaining satisfied, productive employees.

To realise that vision, companies must close the gap between knowing and doing, from collecting thousands of data streams and knowing what they contain to applying decision-making frameworks to each of them. Companies can progress on that journey by acting on data insights through an analytics operation that uses digital workflows as its building blocks and adds layers of intelligence in three phases:

#1 Workflows from data

Digital workflows and the data they generate make every part of a process visible. Take customer behaviour, for example. With a data-collection platform in place, analytics teams today can start closing the knowing or doing gap by building workflow playbooks triggered by specific insights in the customer journey. The playbooks, in turn, flow into real-time analytics that customer service teams can easily see or be alerted to when customers hit a snag with any aspect of these tracked behaviours. 

#2 Apply analytics 

The next step is to apply analytics to those individual data workflows to produce a deeper layer of actionable insights. The dashboard view into data workflows offers relevant information about all sorts of variables, so customer teams are able to act on multiple issues instead of just one.

#3 Workflow master view 

Applying analytics to the foundation built with the first two steps can offer executives a potential data gold mine: a highly actionable, digital view into core KPIs and company performance at an enterprise level. It starts with simple math. 

Let’s say you have 30,000 customers and you are tracking 15 workflows per customer per year. These workflows impact an average of 10 types of company employees. The analytics supporting all that is now tracking 15 million tasks or steps in all the workflows you have deemed most important to the business. That’s a 360-degree, data-enabled view into the entirety of work being done, analysed over any time period. Workflow-powered analytics can give everyone in the C-suite the same kind of dashboard for the business that our customer-facing teams use so successfully.

While no company can pull this off overnight, digital platforms and tools now enable organisations to build intelligent analytics largely by themselves. They can start optimising the most critical operations and continually convert insight into action.

Key takeaways

• The global market for data analytics platforms and tools reached $200 billion in 2019, according to IDC.
• The promise of modern analytics is to improve decision-making in support of critical business objectives.
• Building workflows from data, applying analytics, creating master view of workflow are three phases.