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Overview

Unexpected failure or performance erosion of production equipment can significantly impact productivity, product quality and maintenance expenses within any manufacturing organization. It’s also difficult to get operations ‘back on track’ after these failures occur. The good news is that, via the Internet of Things, intelligent use of sensor data, machine learning and optimization can help companies take a proactive approach to predicting failures and re-optimizing processes around them. 

This Q&A with Dr. Michael Watson, Partner at Opex Analytics and Adjunct Professor at Northwestern University, discusses:

  • The evolution of sensors in manufacturing plants, and their increased use as costs decrease
  • How some manufacturers are getting more creative with sensor data – evolving from predictive to prescriptive (optimization) analytics to drive better actions
  • How an optimization-powered approach can help you not only better predict failure, but also determine what to fix today vs. later (or not at all)
Overview

With the term “Big Data” now commonplace, there’s no mistaking that today’s volume, variety and velocity of data challenges organizations that follow splintered approaches to data connection, ingestion, processing and analysis. Too many IT departments are still falling short of transcending legacy approaches that limit the value they derive from data. Typically, those organizations find themselves caught in differentiating data treatment by type — particularly between batch and streaming data — and consequently supporting disparate IT infrastructures. That seriously misaligns those organizations with contemporary data realities, and it short-circuits opportunity. 

For Industries: 
Technology
Overview

A proliferation of data and the invention of new technologies are combining to change the very way people make decisions. These forces are also changing the very nature of the decisions we make.

For Industries: 
Banking
Overview

Credit markets have seen many changes in recent years, including tremendous innovation, the rise of marketplace lenders around the globe and new credit products from major technology players such as Amazon. That innovation is driving existing lenders to rethink their infrastructure and processes to become more nimble while regulators begin focusing on the new entrants (e.g., The US Treasury Department recently issued a whitepaper on potential disparate impact and fair lending for marketplace lenders). These changes require traditional firms to be agile and adapt quickly to new innovation, new players and new regulation, all the while improving the customer experience. 

Tim Van Tassel, Vice President and General Manager of FICO’s Credit Risk practice, weighs in on the subject of how marketplace lending is changing the credit landscape, and what that means for both new marketplace lenders and traditional credit-grantors. 

Overview

Optimizing supply chain strategies and network designs keeps getting harder, with persistent challenges from increasing customer demands, spiraling costs, disruptive competitors and multifaceted partnership and logistical options. 

Spreadsheets and BI aren’t enough to deal with the complexity and business and logistical nuances in your business. The good news that it’s never been easier – or faster – to deploy powerful optimization to address your most challenging supply chain and logistics challenges. FICO® Optimization Solutions for Supply Chain helps businesses like Shell, Honeywell, Nestle, Southwest Airlines and others dynamically and proactively manage all critical processes within your supply chain lifecycle. They do this in two critical ways: by substantially reducing the time to develop and deploy optimized supply chain solutions by as much as 80%, while increasing visibility into every critical facet of your supply chain via dashboards and other visualization tools.

Overview

Historically, manufacturers have “looked to the past” to help predict what they need to do in the future. This would include basic business intelligence, powered by spreadsheets, and even manual processes. The challenge is that what will happen may be something outside of what the past can predicts – who, 25 years ago, would have considered the Internet as a primary vehicle for commerce, or that Big Data would become both a treasure and a tragedy for organizations? Consider other factors, such as regulations, largely transient customers (where loyalty and brand aren’t what they used to be), disruptors (such as new entrants and technologies), and the need for manufacturers to “move faster than ever” – in effect, to be able to plan for the future before it happens.

This brief dives into how FICO Optimization can help manufacturers deploy optimization solutions up to 80% faster than before, while empowering frontline staff, business analysts and data scientists to collaborate to solve your hardest problems. Also:

  • Discover new opportunities to drive margin and efficiency in areas never before possible with other analytic tools and enterprise software.
  • Leverage insights to plan for the future, and quickly make changes that address immediate needs or conditions.
  • Readily import data from your analytic tools, ERP software, spreadsheets and MES into your optimization framework, so you don’t need to “rip and replace” your existing infrastructure.
  • Unlock the hidden value of your data by leveraging multiple data sources, in-stream or at-rest, within your analytic decisioning framework.
Overview

Companies are increasingly turning to data and analytics for competitive advantage. But more than 70% of enterprises report struggling to achieve consistently positive results despite spending more to build, maintain and analyze ever-larger data repositories.1 This may be because they are using the wrong approach. Rather than start with data, companies should apply a decision-first approach that begins with the business objective and decision model before considering data and analytic requirements. FICO® DMN Modeler and FICO® Decision Management Suite make creating, managing and executing clear decision models faster and easier than ever before. 

Overview

Strategic decisions drive success and the process of managing, automating and improving these decisions has become crucial for companies across all industries. Decision analysis techniques help companies make smart, timely decisions and decision trees are a good example of technology that can help determine the best decision. But the technology is just one of the critical elements of a decision strategy. You have to know how to think about the problem you’re trying to solve and how to design an effective strategy. And once you have a solid strategy in place, it’s important to continue taking a fresh look at your data, your rules and your strategies on a regular basis. You can use data, tools and analytic techniques to understand current results then redevelop strategies for continual improvement. 

Overview

The increasing number, variety, speed and severity of cyber attacks calls for a new line of defense. While there are many signature-based solutions for protecting against known cyber attack vectors, the key gap is identifying threats for which no signature has yet been isolated. Better defenses are also needed to protect against attacks involving credential changes after spear phishing. To minimize losses, we must detect and stop threats based on the abnormal behaviors they exhibit in the network, as they occur. To prevent losses, we must predict and stop as many threats as possible during the reconnaissance period, before data is exfiltrated.

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