Big data is often viewed as the Holy Grail. It has a certain “je ne sais quoi” that inspires wonder and awe. But data can’t do it alone. Unregulated production and collection of big data creates huge oceans of data (sometimes called data lakes). To make this data meaningful, it must be organized and analyzed and, most importantly, acted upon.
Even with analysis employed, it is often difficult to determine which data is of high value and which is just noise. Historical analysis and batch processing of the data are a good start, but more is needed to keep up with the velocity of business and to understand within a moment’s notice how to use this data to gain new clients and capitalize on market opportunities.
Real-time analytic use cases continue to make headlines
- St. John’s River in Florida is rolling out a real-time data system to improve safety and reliability of maritime business
- Chinese internet giant Baidu is using big data to forecast the flu
- Grocery store chain Kroger is fully instrumenting the shopping experience to better understand their clients and the products they consume, allowing the chain to deliver real-time marketing offers and optimize inventory
Kroger, and many other grocery store chains like it, are facing increased competition in new business models like personal shopping services and order-ahead grocery pick up. These new models are keeping consumers out of the stores and, as a result, grocery stores are losing the very lucrative impulse purchase revenue which they have relied on for so long. Traditional methods of marketing, such as plastering signs outside the store, distributing circulars and mailing coupons via the US postal service, are quickly becoming antiquated.
The key is real-time actionable insight in the business moment
To test this theory, we asked several clients about their speed of response time for promotions and offers. Unfortunately, the numbers were weak: one telecommunications provider analyzed seven million messages per second, but took weeks or months to complete a promotion based on the analysis; another client took up to two weeks to intelligently respond to sentiment on social media.
The ability to act on insights derived from big data sounds complex, but IBM has built a solid foundation which acquires, grows and retains more clients in the business moment. This real-time actionable insight platform is built on four pillars that help organizations constantly analyze the world around them. This sensing in the now facilitates intelligent optimization of decisions, processes, systems and points of interaction in the business moment.
The four pillars which construct this solid structure:
Today, we focus on the first element: Sense
According to Merriam-Webster, sense means “the faculty of perceiving.” To illustrate sense, let’s consider the example of “orange” for a moment. Through the five senses, humans begin to perceive what orange is based on context: it could be a color, a fruit, a French telecommunications provider or a reference to the Orangemen of Syracuse. However, it is far more challenging to sense context in big data, where the typical human senses do not reign supreme.
IBM technology is able to pay very close attention to each observation as it enters the enterprise. These observations incrementally improve existing knowledge and dynamically update an emerging view of reality to activate higher quality business decision-making. Some core capabilities of sensemaking technology include:
- Sequence neutrality at scale: Understand context as volumes, speeds and size increase
- Privacy by design: Keep sensitive information safe
- High tolerance for uncertainty: Understand what is happening despite untrusted data
- Geospatial awareness: Know exact location of data sources
- Selective curiosity: Provide recommendations for observations and data points that might be relevant in the business moment
- Diverse perspective: Allow different users to explore context in their own way
- Accumulation: Remember context over time
For a more technical deep dive on sensemaking, check out this article from IBM Chief Technology Officer for Context Computing, Jeff Jonas: “G2 | Sensemaking and its 7 Secret Sauces.” To continue the conversation, ask yourself these questions:
- How well do you sense context in your organization?
- As you receive a new data point, how do you evaluate it against what you know already?
- Can you, in real time, ingest, correlate and find meaning in the data?
The next installment in this five-part series will explore Orient: the ability to use real-time analytics together with historical data, past experiences and known data to create an accurate picture of potential business opportunities appropriate for the business moment. Tell us what you think: How important is sensing context to you and your business? Use #IBMChickenDinner to insert your thoughts into the social conversation.
For more reading, explore the links below:
- The rise of machine data, are you prepared
- Empower security analysts with deep analytics
- What do chicken dinners have to do with IBM?
- Join us at IBM Insight for hands on learning