Orient: Analyzing data in the business moment
Don't go chasing wild chickens
Big data can be turned into big business opportunities, but can also send you on a wild goose (or, in this case, chicken) chase.
This series of blog posts focuses on IBM’s four pillar approach to real-time actionable insight (sense, orient, decide and act) and how to shift from reactive to proactive mode, effectively orienting your organization to the business moment. Catch up on post one and two in the series.
Coming to your senses
Humans use all five senses to understand and interpret events in both their personal and business lives. Sight, sound, taste, touch and smell continuously handle big data problems and automatically trigger the right action with little delay (think fight or flight response) or the memories triggered by a particular sound or smell (for example, I always think the Pittsburgh Pirates scored a home run when I hear fireworks in the summer). In short, humans have evolved to thrive in big data environments.
Sensing in a business environment is no different. Organizations should gather observations from all possible sources (such as the Internet of Things, social media, images and structured data stores) to support an automatic action optimized for the best business outcome.
Making sense out of diverse observations streaming from different sources at different speeds is the first step to help you acquire, grow and retain more clients. For example, if you know that a large group of people is within three miles of your retail establishment, you might want to send them a real-time offer to entice them to come and spend. This type of offer requires organizations to first sense what’s happening right now (people passing by the store, for example) and next orient quickly before the group is out of range—the orient step is what we'll focus on here.
Orient to the business moment
Consulting dictionary.com, we know orient means “to familiarize with new surroundings or circumstances.” Big data analytics is one way to orient to the business moment, especially real-time analytics that can ingest, analyze and correlate fast-moving information with sub-millisecond responses. Orient brings together historical data, past experiences and known characteristics to analyze them together with real-time streaming data and create an accurate picture of potential business opportunities.
Let’s revisit our retail example. Our retailer needs to marry real-time geospatial data and time of day with propensity to buy models and business rules. This marriage will help them to understand which people are potential clients, and if a marketing offer would be profitable or if some other engagement model or response is preferred.
It isn’t good enough to just know that a customer is nearby (this is input from the sense step). The retailer also needs to know the right discount and surround offers to send. Therefore, a technology that merges real-time geospatial and time data with predictive models and business rules is the right approach. We probably don’t want to send an offer for a free cup of coffee at 10 p.m., or a coupon for a discounted chicken dinner if the person is now 30 miles away from the grocer.
A few examples of real-time analytic techniques required to orient your business include:
- Geospatial analytics
- Image or video facial recognition
- Time series analysis
- Social data analytics
- Statistical models
The real-time analytics will dynamically update business, predictive and prescriptive models. Visualizing opportunities to acquire, grow and retain clients is also part of the orient step. For example, our retailer should be able to visualize potential clients on a map and how they are moving through space in real time. They might also want to understand which consumers have opted in to receive marketing campaigns.
Sense, orient, decide and act
IBM’s four pillar approach for real-time actionable insight (sense, orient, decide, act) is actually based on the OODA loop developed by military strategist and USAF Colonel John Boyd. Boyd applied the concept to the combat operations process, often at the strategic level in military operations. It is now also often applied to learning processes; we believe it’s important to apply these cognitive techniques to big data technologies as well.
We hope you will join us next week to learn more about what happens when you Decide, our upcoming third post in the series and the third column that builds real-time actionable insight. For the interim, enjoy the reading below and catch up on social using #IBMChickenDinner:
- The next revolution in decision management: Capturing big data
- The Forrester Wave: Big Data Streaming Analytics Platforms, Q3 2014
- Real-time actionable insight and decision-making with be key points of focus at IBM Insight 2014—register today!