Predictive analytics uses technology to predict the future and influence it. Organizations can use historical performance data to extrapolate and make predictions about the future and take actions that would affect those results.
A great explanation and discussion of predictive analytics can be found in the video below:
As Dr. Siegel states, predictive analytics is unique in that it predicts a predefined behavior at an individual level. Organizations can set in place specific conditions, which when met would allow an analyst to identify an individual’s behavior such as a customer’s willingness to return to a store, or a voter’s flexibility to be persuaded into voting for a particular candidate, etc. Dr. Siegel explains that each individual person can be assigned a predictive score as to the behavior that might be valuable for that organization to predict. This behavior may help drive operations for a business or simply offer insights on future events.
Predictive analytics differs from traditional business intelligence initiatives in that it adopts a proactive approach to data. Traditional B.I. initiatives use data to learn about a customer or to identify trends in a business. Predictive analytics identifies how that customer will behave in a future situation and how they may react to the various “touchpoints” a business has with them. The distinction lies in the ability to almost automatically discover patterns in data that show problems and identify opportunities. Predictive analytics empowers organizations to plan for the future, which can transform an uncertainty into a usable action with high probability.
The ability to predict the future and influence it is a lucrative opportunity and companies such as IBM and SAP are great examples of organizations that adopt this initiative. IBM uses predictive analytics software to increase profitability, prevent fraud, and even measure the social media impact of marketing campaigns. SAP allows customers to act on big data and offers insights on new opportunities and any hidden risks. Predictive analytics also extends beyond these two companies to various industries some of which are listed below.
Predictive Analytics in Various Industries
Customers who shop online enjoy a seamless, immersive experience that features price and product comparisons, reviews from other customers, and recommendations based on preferences and purchase history. In order to deliver these features online retailers are required to analyze, process, and act based on a myriad of metrics. Online retailers can benefit from using predictive analytics to drive predictive search or offer recommendations to their customers.
Predictive search, as explained in this article, focuses on a consumer’s interaction with an online retailer when they do “site search.” Consumer’s often times visit retail websites to find a particular product or service, and with predictive search an online retailer can use past click-through behavior, and preferences to identify relevant content (product or service) that would be of interest to the consumer. The use of predictive software in this case, records a consumer’s past behavior and intends to identify future product searches. Online Retailers can also use similar predictive analytics software to recommend products or promotions that may help generate a sale. A key benefit of predictive analytics in online retail is the real-time processing of such data, which offers content based on a consumer’s past and current browsing behavior.
Predictive analytics in healthcare involves a much larger scale of metrics and data points, but as Dr. Siegel states, “More data equals more opportunity to learn.” Healthcare professionals can use predictive analytics to process a patient’s data, and forecast the potential for illness. This predictive measure would allow patients to not only benefit from early prognosis of ailments, but would also reduce healthcare costs in the future. Predictive analytics can also help healthcare organizations identify high-risk patients, reduce hospital readmission rates, and reduce future costs by promoting healthy behavior. It is important for healthcare professionals to identify illnesses at an early stage, but with predictive analytics the healthcare industry can benefit by encouraging healthy initiatives that reduce the number of illnesses in the first place.
IBM’s Watson solution offers clinical insights that integrate structured and unstructured data with their predictive analytics software. It enables healthcare professionals by applying “predictive root cause analysis, natural language processing” that help identify trends and patterns in healthcare.
For more information about applying predictive analytics to healthcare, please click here.
Predictive Analytics also has a future in education. Educational institutes are in a constant struggle with rising costs attributed to high-tech infrastructure and amenities, which differentiate schools from their competitors and attract new students. In order to differentiate themselves, institutes need to identify and understand the needs of their students. Schools can use predictive analytics software to identify completion rates, student success after graduation, and even personalize the learning process for students.
Educational institutes can also use predictive analytics to identify the needs of existing students or teachers. By catering to the specific needs of their teachers, institutes can improve operational efficiency and drive academic success. Schools can also target a student’s needs in regards to loans and scholarships, which would reduce the risk of financial strain after graduation. Institutes can offer programs and opportunities that allow students to cultivate an area of interest and gain valuable experience in their fields.
Predictive Analytics offers a unique opportunity to identify future trends and allows organizations to act upon them. As Dr. Siegel states, data is the “collective experience of an organization” and building machines that can harness such data in order to find patterns that hold true in new situations is important. With a growth in big data and the evolving nature of Business Intelligence, predictive analytics can offer valuable insights for organizations.
For more information on Predictive Analytics, please view the slides below:
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