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Using Predictive Analytics For Planning, Forecasting – And Decision-Making

Henner Schliebs

In a global survey of 1,544 CFOs and finance executives by CFO Research, three-quarters anticipate making effective use of Big Data over the next five years. Finance organizations will need to make significant changes in their processes, skills, and technology to use this data to their advantage.

The best finance organizations are using predictive analytics to forecast future performance and drive strategic decision-making. To be clear, predictive analytics refers to the organizational capability to discover and communicate meaningful patterns in data to predict and improve business performance, recommend action, and guide decision-making. Rather than relying primarily on historical information, finance organizations can use predictive analytics to identify trends, analyze key variables, examine what-if scenarios, and so on – live.

Here are some examples of how the smart use of predictive analytics has contributed to the success of some companies and enhanced the impact of the finance organization.

Increasing forecasting frequency, reducing cycle time

Many Americans look to the American Automobile Association (AAA) for travel assistance, insurance, and emergency towing. To optimize service from the AAA motor clubs across the United States and Canada, the AAA national office built a centralized “action center” to provide better insight into member needs. With next-generation predictive analytics, AAA could better understand customers’ needs by having real-time access to data. This led to enhanced marketing campaigns and reduced customer attrition rate.

Live Oak Bank lends exclusively to small businesses and specific professions like veterinarians and pharmacists, and due to the nature of these customers, the bank values speed and flexibility. The bank is guided by executives who are industry leaders in both finance and technology, bringing innovation and efficiency to the lending process. The bank leverages real-time analytics to make better decisions more quickly. With the predictive analytics platform, decision-makers now enjoy greater collaboration and transparency, and the team can respond quickly to managers.

As the UK’s largest insurer and a leading provider of insurance and asset management, Aviva protects around 31 million customers worldwide with insurance, savings, and investment products. Tapping into predictive analytics models helped Aviva gain the insight needed to serve clients with offers most relevant to their interests. The company made use of predictive analytics to generate propensity models for more targeted customer groups, rather than a generic group, which allowed staff members to make better decisions and more accurate projections for clients.

One of the world’s most renowned manufacturers of skylights, VELUX from Denmark, uses predictive finance to optimize the balance sheet by better understanding the financial impact of warranty claims, and therefore improve customer service.

Use cases for different financial processes can add some ideas to your agenda.

Harnessing unstructured data

Traditionally, software has been useful in reading and analyzing structured data, but the volume of unstructured data – from external financial reporting systems, RFID sensors, and social media, for example – is exploding. Predictive analytics can help CFOs harness it for more accurate planning, forecasting, and decision making based on what’s happening now and what’s likely to happen, rather than what happened in the past.

To learn more about how finance executives can empower themselves with the right tools and play a vital role in business innovation and value chain, review the SAP finance content hub, which offers additional research and valuable insights.

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About Henner Schliebs

Henner Schliebs is the Vice President and Head of Global Finance Audience Marketing at SAP. He is a progressive sales/marketing executive with 15+ years business software solutions focused on corporate functions, offering superb marketing and Go To Market skills and proven track record in enterprise software solutions, along with significant experience in solution management and customer engagement.

Real-Time Analysis Tools Critical To Improving Finance Performance [INFOGRAPHIC]

Viki Ghavalas

The majority of finance executives agree that real-time analysis tools are key to making better business decisions, according to a report by CFO Research and SAP titled “The Future of Financial Planning and Analysis.” However, executives polled also believe that their current systems still need more improvement to be able to make a positive impact on the business. Executives surveyed point to four main priorities for their FP&A tools.

Finance executives surveyed expect the demand for real-time analysis tools to grow in the coming years. However, the survey also shows that having these tools is not enough and that stakeholders also expect analysis and insights from finance that are simple and actionable.

Data in financial planning and analysis

Learn more about what finance executives are projecting for FP&A by downloading the “The Future of Financial Planning and Analysis” report.

Are you monitoring business performance in real time? If not, read Boosting Efficiency For CFOs And The Finance Function.

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About Viki Ghavalas

Viki Ghavalas is worldwide program manager for the finance line of business at SAP.

Why Banks Should Be Bullish On Integrating Finance And Risk Data

Mike Russo

Welcome to the regulatory world of banking, where finance and risk must join forces to banking executiveensure compliance and control. Today it’s no longer sufficient to manage your bank’s performance using finance-only metrics such as net income. What you need is a risk-adjusted view of performance that identifies how much revenue you earn relative to the amount of risk you take on. That requires metrics that combine finance and risk components, such as risk-adjusted return on capital, shareholder value added, or economic value added.

While the smart money is on a unified approach to finance and risk, most banking institutions have isolated each function in a discrete technology “silo” complete with its own data set, models, applications, and reporting components. What’s more, banks continually reuse and replicate their finance and risk-related data – resulting in the creation of additional data stores filled with redundant data that grows exponentially over time. Integrating all this data on a single platform that supports both finance and risk scenarios can provide the data integrity and insight needed to meet regulations. Such an initiative may involve some heavy lifting, but the advantages extend far beyond compliance.

Cashing in on bottom-line benefits

Consider the potential cost savings of taking a more holistic approach to data management. In our work with large global banks, we estimate that data management – including validation, reconciliation, and copying data from one data mart to another – accounts for 50% to 70% of total IT costs. Now factor in the benefits of reining in redundancy. One bank we’re currently working with is storing the same finance and risk-related data 20 times. This represents a huge opportunity to save costs by eliminating data redundancy and all the associated processes that unfold once you start replicating data across multiple sources.

With the convergence of finance and risk, we’re seeing more banks reviewing their data architecture, thinking about new models, and considering how to handle data in a smarter way. Thanks to modern methodologies, building a unified platform that aligns finance and risk no longer requires a rip-and-replace process that can disrupt operations. As with any enterprise initiative, it’s best to take a phased approach.

Best practices in creating a unified data platform

Start by identifying a chief data officer (CDO) who has strategic responsibility for the unified platform, including data governance, quality, architecture, and analytics. The CDO oversees the initiative, represents all constituencies, and ensures that the new data architecture serves the interests of all stakeholders.

Next, define a unified set of terms that satisfies both your finance and risk constituencies while addressing regulatory requirements. This creates a common language across the enterprise so all stakeholders clearly understand what the data means. Make sure all stakeholders have an opportunity to weigh in and explain their perspective of the data early on because certain terms can mean different things to finance and risk folks.

In designing your platform, take advantage of new technologies that make previous IT models predicated on compute-intensive risk modeling a thing of the past. For example, in-memory computing now enables you to integrate all information and analytic processes in memory, so you can perform calculations on-the-fly and deliver results in real time. Advanced event stream processing lets you run analytics against transaction data as it’s posting, so you can analyze and act on events as they happen.

Such technologies bring integration, speed, flexibility, and access to finance and risk data. They eliminate the need to move data to data marts and reconcile data to meet user requirements. Now a single finance and risk data warehouse can be flexible and comprehensive enough to serve many masters.

Join our webinar with Risk.net on 7 October, 2015 to learn best practices and benefits of deploying an integrated finance and risk platform.

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About Mike Russo

Mike Russo, Senior Industry Principal – Financial Services Mike has 30 years experience in the Financial Services/ Financial Software industries. His experience includes stints as Senior Auditor for the Irving Trust Co., NY; Manager of the International Department at Barclays Bank of New York; and 14 years as CFO for Nordea Bank’s, New York City branch –a full service retail/commercial bank. Mike also served on Nordea’s Credit, IT, and Risk Committees. Mike’s financial software experience includes roles as a Senior Banking Consultant with Sanchez Computer Associates and Manager of Global Business Solutions (focused on sale of financial/risk management solutions) with Thomson Financial. Prior to joining SAP, Mike was a regulator with the Federal Reserve Bank in Charlotte, where he was responsible for the supervision of large commercial banking organizations in the Southeast with a focus on market/credit/operational risk management. Joined SAP 8years ago.

The Robotics Race

Stephanie Overby

As robotic technologies continue to advance, along with related technologies such as speech and image recognition, memory and analytics, and virtual and augmented reality, better, faster, and cheaper robots will emerge. These machines – sophisticated, discerning, and increasingly autonomous – are certain to have an impact on business and society. But will they bring job displacement and danger or create new categories of employment and protect humankind?

We talked to SAP’s Kai Goerlich, along with Doug Stephen of the Institute for Human and Machine Cognition and Brett Kennedy from NASA’s Jet Propulsion Laboratory, about the advances we can expect in robotics, robots’ limitations, and their likely impact on the world.

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qa_qWhat are the biggest drivers of the robot future?

Kai Goerlich: Several trends will come together to drive the robotics market in the next 15 to 20 years. The number of connected things and sensors will grow to the billions and the data universe will likewise explode. We think the speed of analytics will increase, with queries answered in milliseconds. Image and voice recognition – already quite good – will surpass human capabilities. And the virtual and augmented reality businesses will take off. These technologies are all building blocks for a new form of robotics that will vastly expand today’s capabilities in a diversity of forms and applications.

Brett Kennedy: When I was getting out of school, there weren’t that many people working in robotics. Now kids in grade school are exposed to a lot of things that I had to learn on the job, so they come into the workplace with a lot more knowledge and fewer preconceptions about what robots can or can’t do based on their experiences in different industries. That results in a much better-trained workforce in robotics, which I think is the most important thing.

In addition, many of the parts that we need for more sophisticated robots are coming out of other fields. We could never create enough critical mass to develop these technologies specifically for robotics. But we’re getting them from other places. Improvements in battery technology, which enable a robot to function without being plugged in, are being driven by industries such as mobile electronics and automotive, for example. Our RoboSimian has a battery drive originally designed for an electric motorcycle.

qa_qDo you anticipate a limit to the tasks robots will be able to master as these core technologies evolve?

Goerlich: Robots will take over more and more complex functions, but I think the ultimate result will be that new forms of human-machine interactions will emerge. Robots have advantages in crunching numbers, lifting heavy objects, working in dangerous environments, moving with precision, and performing repetitive tasks. However, humans still have advantages in areas such as abstraction, curiosity, creativity, dexterity, fast and multidimensional feedback, self-motivation, goal setting, and empathy. We’re also comparatively lightweight and efficient.

Doug Stephen: We’re moving toward a human-machine collaboration approach, which I think will become the norm for more complex tasks for a very long time. Even when we get to the point of creating more-complex and general-purpose robots, they won’t be autonomous. They’ll have a great deal of interaction with some sort of human teammate or operator.

qa_qHow about the Mars Rover? It’s relatively autonomous already.

Kennedy: The Mars Rover is autonomous to a certain degree. It is capable of supervised autonomy because there’s no way to control it at that distance with a joystick. But it’s really just executing the intent of the operator here on the ground.

In 2010, DARPA launched its four-year Autonomous Robotic Manipulator Challenge to create machines capable of carrying out complex tasks with only high-level human involvement. Some robots completed the challenge, but they were incredibly slow. We may get to a point where robots can do these sorts of things on their own. But they’re just not as good as people at this point. I don’t think we’re all going to be coming home to robot butlers anytime soon.

Stephen: It’s extremely difficult to program robots to behave as humans do. When we trip over something, we can recover quickly, but a robot will topple over and damage itself. The problem is that our understanding of our human abilities is limited. We have to figure out how to formally define the processes that human beings or any legged animals use to maintain balance or to walk and then tell a robot how to do it.

You have to be really explicit in the instructions that you give to these machines. Amazon has been working on these problems for a while with its “picking challenge”: How do you teach a robot to pick and pack boxes the way a human does? Right now, it’s a challenge for robots to identify what each item is.

qa_qSo if I’m not coming home to a robot butler in 20 years, what am I coming home to?

Goerlich: We naturally tend to imagine humanoid robots, but I think the emphasis will be on human-controlled robots, not necessarily humanshaped units. Independent robots will make sense in some niches, but they are more complex and expensive. The symbiosis of human and machine is more logical. It will be the most efficient way forward. Robotic suits, exoskeletons, and robotic limbs with all kinds of human support functions will be the norm. The future will be more Iron Man than Terminator.

qa_qWhat will be the impact on the job market as robots become more advanced?

SAP_Robotics_QA_images2400x16004Goerlich: The default fear is of a labor-light economy where robots do most of the work and humans take what’s left over. But that’s lastcentury thinking. Robots won’t simply replace workers on the assembly line. In fact, we may not have centralized factories anymore; 3D printing and the maker movement could change all that. And it is probably not the Terminator scenario either, where humanoid robots take over the world and threaten humankind. The indicators instead point to human-machine coevolution.

There’s no denying that advances in robotics and artificial intelligence will displace some jobs performed by humans today. But for every repetitive job that is lost to automation, it’s possible that a more interesting, creative job will take its place. This will require humans to focus on the skills that robots can’t replicate – and, of course, rethink how we do things and how the economy works.

qa_qWhat can businesses do today to embrace the projected benefits of advanced robotics?

Kennedy: Experiment. The very best things that we’ve been able to produce have come from people having the tools an d then figuring out how they can be used. I don’t think we understand the future well enough to be able to predict exactly how robots are going to be used, but I think we can say that they certainly will be used. Stephanie Overby is an independent writer and editor focused on the intersection of business and technology.

Stephanie Overby  is an independent writer and editor focused on the intersection of business and technology

To learn more about how humans and robots will co-evolve, read the in-depth report Bring Your Robot to Work.

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What Is The Key To Rapid Innovation In Healthcare?

Paul Clark

Healthcare technology has already made incredible advancements, but digital transformation of the healthcare industry is still considered in its infancy. According to the SAP eBook, Connected Care: The Digital Pulse of Global Healthcare, the possibilities and opportunities that lie ahead for the Internet of Healthcare Things (IoHT) are astounding.

Many health organizations recognize the importance of going digital and have already deployed programs involving IoT, cloud, Big Data, analytics, and mobile technologies. However, over the last decade, investments in many e-health programs have delivered only modest returns, so the progress of healthcare technology has been slow out of the gate.

What’s slowing the pace of healthcare innovation?

In the past, attempts at rapid innovation in healthcare have been bogged down by a slew of stakeholders, legacy systems, and regulations that are inherent to the industry. This presents some Big Data challenges with connected healthcare, such as gathering data from disparate silos of medical information. Secrecy is also an ongoing challenge, as healthcare providers, researchers, pharmaceutical companies, and academic institutions tend to protect personal and proprietary data. These issues have caused enormous complexity and have delayed or deterred attempts to build fully integrated digital healthcare systems.

So what is the key to rapid innovation?

According to the Connected Care eBook, healthcare organizations can overcome these challenges by using new technologies and collaborating with other players in the healthcare industry, as well as partners outside of the industry, to get the most benefit out of digital technology.

To move forward with digital transformation in healthcare, there is a need for digital architectures and platforms where a number of different technologies can work together from both a technical and a business perspective.

The secret to healthcare innovation: connected health platforms

New platforms are emerging that foster collaboration between different technologies and healthcare organizations to solve complex medical system challenges. These platforms can support a broad ecosystem of partners, including developers, researchers, and healthcare organizations. Healthcare networks that are connected through this type of technology will be able to accelerate the development and delivery of innovative, patient-centered solutions.

Platforms and other digital advancements present exciting new business opportunities for numerous healthcare stakeholders striving to meet the increasing expectations of tech-savvy patients.

The digital evolution of the healthcare industry may still be in its infancy, but it is growing up fast as new advancements in technology quickly develop. Are you ready for the next phase of digital transformation in the global healthcare industry?

For an in-depth look at how technology is changing the face of healthcare, download the SAP eBook Connected Care: The Digital Pulse of Global Healthcare.

See how the digital era is affecting the business environment in the SAP eBook The Digital Economy: Reinventing the Business World.

Discover the driving forces behind digital transformation in the SAP eBook Digital Disruption: How Digital Technology is Transforming Our World.

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About Paul Clark

Paul Clark is the Senior Director of Technology Partner Marketing at SAP. He is responsible for developing and executing partner marketing strategies, activities, and programs in joint go-to-market plans with global technology partners. The goal is to increase opportunities, pipeline, and revenue through demand generation via SAP's global and local partner ecosystems.