Innovation Alphabet

Advanced Analytics

In a nutshell

The term “Advanced Analytics” refers to the ability to autonomously or semi-autonomously analyze data and content to identify correlations, develop analyses, predictions, and recommendations. It is not just a matter of collecting information and then organizing it into watertight compartments: the ultimate goal is to identify a dialogue pattern from a data-driven perspective.

An array of test tubes as the Advanced Analytics quickcard header image
Application Fields

Sports activity: Most smartphones support apps that monitor physical activity, but the study of big data promises to improve even performance. Through advanced analytics solutions, it is possible to prevent overexertion and injuries, set up hyper-personalized training sessions and thus enrich the sports experience.

Digital Marketing: As easily predictable, in digital marketing big data assume an indispensable role. For example, they “anticipate” customer needs. A huge amount of information is collected from a huge amount of sources (business systems, e-commerce portals, social media…). This way, advertisers and merchants can initiate promotional campaigns and sales strategies customized to each type of buyer.

Banking Industry: Advanced analytics tools can be used in loan and mortgage origination to optimize fraud prevention. Through credit ratings, banks can accelerate the customer assessment process. This confirms the viability of a loan or identifies profiles that, due to credit history and financial behavior, represent a higher risk. Gartner broke down fraud prevention into five layers:

Gartner’s 5-Layered Fraud Prevention Approach
Industries

• Advanced Analytics in the healthcare industry
Four of the hospitals that make up the Assistance Publique-H’pitaux de Paris (AP-HP) have adopted an Advanced Analytics system. Through machine learning and big data solutions, it aspires to predict the rate of hospitalization 15 days in advance. In the event of a spike in visits and admissions, hospitals would employ more staff to reduce waiting times and better manage patients. Losses could thus be reduced, and health insurance would gain in efficiency.

Advanced Analytics in the energy industry
Shell, a major global player in the oil and natural gas industry, is using data to drive its own organizational change. For example, working with Microsoft, the company has designed a collaborative digital platform through which it can monitor not only its own sustainability initiatives, but also those of its suppliers. Shell’s long-term goal is not to drive digital transformation, but energy transformation. Thanks to Advanced Analytics, the company is going to evolve the industry toward sustainable energy solutions.

Advanced Analytics in the service industry
The Amsterdam Fire Department has used some Advanced Analytics techniques to identify the highest fire risk areas in the city, and improve, as a result, the performance of the city’s fire protection service. How? By combining the government’s open-source data on buildings, roads, waterways and means of transportation with fire department incident reports through sensors placed inside fire hoses and firefighters’ personal protection equipment. This has enabled the service to identify 12 million possible accidents.

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Business Functions

Advanced Analytics in support of marketing
Walmart Stores, the world’s largest retail chain, has created an analytics center to monitor the ROI (Return on Investments) of its marketing campaigns: the Data Café. Data Café enables the rapid modeling, manipulation, and visualization of huge volumes of data. The system provides automatic alerts: if certain metrics fall below set thresholds, the pertinent team is alerted so that the reasons are understood. The Data Café collects information from 200 sources (weather, social media, gas prices, etc.): any detail could be the key to solve a problem.

Advanced Analytics in support of HR
For a long time, Bank of America Corporation experienced some difficulties in keeping its employees responsible for the call center. By using the power of Big Data the company realized that the reason for layoffs was related to inter-office collaboration. Specifically, individual employees’ breaks did not coincide with anyone else’s except during lunch: a scant 15 minutes during which 80 percent of interactions occurred. Interpreting the information gathered, the bank allowed teams of employees to spend their breaks together, unifying their schedules. After a few weeks, call handling time was 23% faster and cohesion had increased by 18%. Translated: $15 million more for the company.

Advanced Analytics in support of management
Metalco, a leading manufacturer of street furniture and dehors, has invested in Advanced Analytics systems to improve demand forecasting in the supply chain. Predictive models capable of creating advanced and automated analytics. These are useful for the company’s managers to obtain information in order to optimize production capacity and thus produce the right quantity of required items. By studying and interpreting the data, demand forecasting has improved by 20 percent.

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