For years, companies have relied on business intelligence (BI) tools to drive strategy and identify opportunities based on historical data. However, in today’s fast-paced, data-driven economy, traditional BI often moves too slowly. Now, with the emergence of the Internet of Things and the demand for greater customer personalization, companies are increasingly striving to quickly make sense of their data as it changes. Operational intelligence – the ability to analyze live, fast-changing data and provide immediate feedback – takes business intelligence to the next level and creates amazing new opportunities.
Using in-memory computing technology allows live, fast-changing data to be stored, updated and analyzed continuously. Ever changing data streams enriched with historical data and then analyzed in parallel provide powerful feedback on the fly. The benefits of operational intelligence are far-reaching and applicable to a wide range of industries, Tincluding manufacturing, cable, and retail.
Operational vs. Business Intelligence
With recent advancements in computing technology, operational intelligence has finally become a reality. While business intelligence provides insights for static datasets, usually identifying long-term trends based on historical data, operational intelligence targets short-lived business opportunities, offering timely, actionable insights. Operational intelligence tracks the behavior of live systems, integrating streaming data with customer preferences and historical information to create a comprehensive view and generate immediate feedback.
Operational intelligence is often confused with “real-time analytics,” which refers to fast, interactive analysis of static data (typically, huge, historical datasets) instead of live data. Accelerating the analysis of static data helps make business intelligence more interactive as it examines important data patterns and long-term trends. However, this still leaves a critical gap between the identification of a pattern and the use of live intelligence to capture business opportunities in the moment. Operational intelligence fills this gap.
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Once implementation challenges have been met, operational intelligence creates exciting opportunities for enhancing the behavior of live systems in diverse industries. Here are a few examples.
In the last few years, factories and plants around the world have added the technology needed to implement operational intelligence. For example, arrays of machines on the factory floor and computing systems within data centers now are able to gather vital, real-time data from sensors and make it available for immediate analysis.
With the use of operational intelligence, analytics systems can continuously compare streams of live data with historical models to monitor performance, identify early indicators of problems, and prevent costly failure scenarios.
Imagine an automotive manufacturing factory that uses hundreds “smart” machines. These machines incorporate tools and sensors that are connected with the company’s network and databases. This provides manufacturing supervisors access to live data, allowing them to use operational intelligence to improve processes and more efficiently achieve operational goals.
For example, operational intelligence can analyze telemetry in real time and thereby anticipate or avoid machine failures. Preventing or detecting machine failures represents a huge area of potential cost savings for manufacturers. The consequential loss that comes with failures quickly builds up, due not only the cost of repair but wasted equipment downtime and a range of inefficiencies that reverberate throughout the business. Rather than solely relying on routine inspections and component replacements, operational intelligence’s analysis of live data cross-referenced with historical data provides greater transparency into the state of equipment health.
Although the explosion of Netflix, HBO GO and other online entertainment options has given viewers more content options than ever before, this abundance of choices makes decision-making daunting for many viewers.
Using operational intelligence, cable providers can track their customers’ program selections, combine this information with historical data and preferences, and make intelligent recommendations in the moment – while the viewer is active. This allows providers to up-sell with appropriate personalized offers. For example, cable providers can alert viewers to upcoming movies and shows that fit their personal preferences. Operational intelligence also enables cable providers to track network behavior, such as bandwidth consumption, and make immediate adjustments that meet the individual needs of each viewer.
Brick and Mortar Retailers
Based on their knowledge of consumer’s shopping habits and previous browsing history, ecommerce retailers like Amazon and eBay are able to make personalized offers and display ads, giving them a huge advantage over brick-and-mortar retailers. The combination of convenience and personalization has seen ecommerce cut into the market share of traditional retailers. The trend looks to continue this holiday shopping season with ecommerce expected to grow 16.6 percent.
Advances in in-memory computing technology, however, may be turning the tide. By combining operational intelligence with recent advancements in mobile technology, in-store retailers now have the tools they need to compete with ecommerce and create a compelling shopping experience. For example, opt-in customers can share their in-store locations with the retailer, which can combine this information with demographics, brand preferences, shopping history, and current offers to assist sales associates in making personalized recommendations that match the customer’s immediate needs.
Moreover, brick-and-mortar stores now are adopting the use of radio frequency identification (RFID) tags to identity every item of merchandise in a store and using the information as part of their operational intelligence. Similar to bar codes, RFID tags identify inventory with high efficiency, enabling stores to track which items customers are examining. This allows sales associates to keep the correct sizes at hand and suggest complementary products. It also reduces the stock that needs to be kept on hand to lower inventory costs.
In-Memory Technology Enables Operational Intelligence
Recent advancements in in-memory computing technology have paved the way for operational intelligence. In-memory computing eliminates the bottlenecks inherent in the techniques used for business intelligence. For example, it avoids the overheads of disk-based data storage and batch scheduling, enabling the immediate, efficient tracking and analysis of live data. Unlike pure streaming and event-processing systems, operational intelligence uses in-memory computing to maintain a comprehensive picture of customer activity, leading to a deeper understanding of behavior, preferences, and customer needs. Moreover, operational intelligence incorporates techniques that ensure uninterrupted processing vital to live, mission-critical environments.
With operational intelligence, companies now are able to analyze the fast-changing data they manage within operational systems, enriching it with historical information and analyzing it for patterns and trends that require immediate action. While business intelligence provide strategic guidance from the data warehouse, operational intelligence acts on the front lines, helping to add value and enhance competitiveness on a second-by-second basis.
Dr. William L. Bain:- Bill has a Ph.D. (1978) in electrical engineering/parallel computing from Rice University, and he has worked at Bell Labs research, Intel, and Microsoft. He founded ScaleOut Software in 2003. Prior to ScaleOut, Bill founded and ran three start-up companies prior to joining Microsoft. In the most recent company (Valence Research), he developed a distributed Web load-balancing software solution that was acquired by Microsoft and is now called Network Load Balancing within the Windows Server operating system. Dr. Bain holds several patents in computer architecture and distributed computing. As a member of the screening committee for the Seattle-based Alliance of Angels, Dr. Bain is actively involved in entrepreneurship and the angel community.
(Featured image credit: David Erickson)