Leveraging analytics from insight to artificial intelligence (AI), business leaders can make sense of their rapidly-growing piles of data to improve their operations. Here are some tips for using analytics to create a measurable business impact. #1: Put the decision before the data With a decision-first strategy you define the business objective first, then determine what data and analytics you need to achieve the goal. Extrapolating insights from huge amounts of data can be interesting, but it can also be a tremendous waste of time and resources if it doesn’t solve a specific business challenge. If the modeling and data analytics requirements are defined by the business outcome first, data exploration and analytic development is faster and more productive. This helps enterprises narrow in on meaningful outcomes, shutting out extraneous noise and focus on the insights that address specific objectives. #2: Get data into decision makers’ hands Empower the business... [Read More]
Optimization of supply chain operations has become an imperative, as organizations grapple with customer demands, unpredictable events, and spiraling costs. On top of these persistent challenges, complexities are magnified by the myriad of tools required to manage everything from workforce schedules to resource allocation. To meet competitive demands, business decisions are needed quickly and accurately against an ever-evolving list of requirements and dependencies. But all too often, supply chains break down in the face of unanticipated factors or messy and incomplete data. To drive greater speed and precision in the supply chain, industry leaders are employing automation technology and visual insight capabilities. This traditional software driven approach can help but does not always suffice in the face of a growing number of variables and constraints. Today, many companies are transforming their supply chain challenges into business opportunities with powerful analytic platforms rooted in Artificial Intelligence and Machine Learning. Machine Learning... [Read More]
The DM3 provides an accurate and actionable segmentation of users and businesses against their current capabilities, requirements, skills and end-state objectives.
Yesterday I had the pleasure of speaking at the Chief Data & Analytics Officer (CDAO) Winter event in Miami. If you’ve ever been to CDAO, you know it is quite a gathering of some of the smartest minds in analytics. Everyone I met had great stories to tell about the innovative work being done with analytics, artificial intelligence (AI) and machine learning (ML). My keynote was focused on using AI, ML and prescriptive analytics to improve business impact and drive optimal outcomes. In partnering with FICO clients, I have found that combining ML with prescriptive analytics solutions delivers the best results when the strategic business outcomes are at the center and are the foundation that influences execution moving forward. Defining a business outcome seems simple enough, but the more prescriptive you can be about what you want to achieve, the more positive impact the solution will have on the business.... [Read More]
Among the major banks in Canada, more than 60% that have already made the transition to the Cloud and we fully expect the others to follow suit in the new year.
Instead of connecting one analytic powered decision solution to another, our customers are asking us to plan out a full, enterprise-wide, centralized decision solution.
In my last post on digital transformation, I talked about how it’s tempting to track your competition in the race to disrupt and transform your industry, but that every business’s DNA mandates an approach specific to your challenges and objectives. When you start to uncover new insights that are transformational, it’s critical to consider one often overlooked fact: You have a lot of hidden data living in your organization that you ultimately need to tap to digitize your business. Where does the data reside? In the brains of your business experts, data scientists — even front and back office staff. And of course, on their PCs, tablets, and even sticky notes and business cards. It’s not just knowledge of their jobs, but the specifics about how they get things done; how they deal with people both in and outside of the company (including customers, partners, vendors and suppliers); and even... [Read More]
With today’s proliferation of data, digital transformation (DX) has become more than a hot topic: It’s an imperative for businesses of all shapes and sizes. The collision of data, analytics and technology has businesses, analysts and consumers excited — and scared — about what could happen next. On one hand, everyone from banks to bagel shops and travel sites to tractor manufacturers have found new ways to connect the dots in their businesses while forging stronger, more dynamic customer engagement. Artificial intelligence (AI) has come of age in technologies such as smart sensors, robotic arms, and devices that can turn lights and heat on and off, adjust for changes in conditions and preferences, and even automatically reorder food and supplies for us. However, today’s Chief Analytics Officer (and Chief Data Officer and Chief Digital Officer, for example) faces both the promise and precariousness of digitizing business. While significant opportunities abound... [Read More]
African Bank, a large retail bank in South Africa, recently went through a large-scale restructuring in order to bring more efficiency, transparency and collaboration to the way it made decisions. Working with FICO, the bank applied a standards-based decision management methodology to fully modernize its decision system. Now that the new solution has been implemented, we spoke with Dawid Van Zyl, Program Executive of Credit Decisioning at African Bank, to learn more. Q: What challenges was African Bank facing with its existing credit decision process? Dawid: Our credit decision lifecycle was fragmented over different applications and teams. This was causing inefficiencies and missed opportunities for our executives to react to the market. We knew we needed to do a complete overhaul of the existing process in order to be effective and profitable. Q: How did you and the FICO team create a solution for this challenge? Dawid: The first step... [Read More]
