Integrated analytics gives users operational intelligence edge

Embedding analytics capabilities in operational processes can pay big business dividends by enabling front-line workers to optimize how things are done, consultant David Loshin says.

Operational intelligence initiatives integrate business intelligence and analytics tools into operational processes to empower business executives and other end users to make better-informed decisions -- leading to higher revenue and profits, if all goes well. They make it possible to monitor business performance in real time, and can proactively alert people on the front lines of an organization to opportunities to improve operations and avoid problems.

Let's look at some of the business processes that can benefit from the actionable information that operational intelligence applications provide:

Embedding the results of analytics applications in the framework of an operational process is what makes the concept so powerful.

Customer service. A call center application can be enhanced by pairing up customer profile data with analytical models evaluating the responses of callers in real time. As a conversation progresses, the probabilities of a customer responding positively to possible promotional offers are calculated, and the call center agent's script can be modified on the fly. Hopefully, the end result is increased customer retention.

Logistics. Deliveries can be made more quickly while improving driver safety through the use of an application that blends spatial data and information on traffic, weather and emergency alerts to calculate the fastest route with the lowest number of issues and hazards. If need be, new routing instructions can be transmitted to a driver's mobile device.

Energy. At a utility company, smart grid data and information on network status, equipment failure patterns and the weather can be combined with sensor-based automated monitoring to preempt electrical grid breakdowns and reroute transmissions as needed. That can help reduce the impact of power outages.

Manufacturing. Productivity can be increased and failures resulting in downtime reduced through real-time monitoring of what's happening on the production floor, courtesy of continuous reporting on the status of assembly-line components. Operations managers can be notified when the metrics indicate an imminent equipment failure and can take preemptive steps to replace parts.

Qualifying criteria for operational gains

So, what are the characteristics of a business process that can benefit from operational intelligence tools and techniques? To qualify, it should have well-defined performance metrics and specific business objectives associated with each metric. There should also be one or more decision points involving one or more of the users involved in the process, along with an internal recognition that business decisions can be impaired by an absence of information -- and that business performance can be impaired by ill-informed decisions. Other criteria include the ability to generate relevant insights by analyzing operational data and to take actions that can improve the business process based on those insights.

It's important to recognize that none of these criteria requires any of the participating users to be technically savvy or have analytics know-how. In fact, embedding the results of analytics applications in the framework of an operational process is what makes the concept so powerful.

To be most effective, though, an operational intelligence initiative should encompass these features:

  • Real-time integration of data from a variety of sources, potentially including both human-generated and machine data -- plus the means to integrate analytics functionality into business processes and their supporting applications in order to get results and drive operational actions in a prescribed window of time
  • Easy-to-grasp data presentation methods suited to specific business roles -- so that, for example, a manufacturing plant floor manager gets a different view of data than a production line operator does
  • Seamless integration with the various devices and applications used by the employees involved in the business process
  • Stream-oriented and event-driven notification, so that the system can send alerts and other messages to the right people in real time

Deployment hurdles to get over

There are challenges to making it all work. Performance is one: A mixed workload of data analysis tasks might have to be run in parallel for different participants in the process. Dealing with increased data volume and velocity is another: A combination of stream processing and big data technologies might be needed to ensure that the required information can be captured and processed in a timely way.

Despite the challenges, the growing adoption of big data systems coupled with the expanding use of sensors and computer-equipped machinery connected to corporate networks via the Internet of Things provides new opportunities for enhancing operational intelligence efforts. More complex analyses can be performed against a broader set of data sources and larger amounts of information. And a greater focus on integrating operational analytics outputs with mobile apps will broaden information delivery capabilities.

Adopting these approaches will help organizations meet the goal of making actionable information accessible to their business operations -- and in time to enable the workers there to take full advantage of that information.

About the author:
David Loshin is president of Knowledge Integrity Inc., a consulting and development services company that works with clients on big data, business intelligence and data management projects. He also is the author or co-author of various books, including Using Information to Develop a Culture of Customer Centricity. Email him at [email protected].

Email us at [email protected] and follow us on Twitter: @BizAnalyticsTT.

Next Steps

Operational intelligence at work in a Texas utility

Real-time analytics brings BI into business operations

Discover more about edge analytics

Edge intelligence is the newborn child of edge analytics, machine learning

Dig Deeper on Operational business intelligence