Using Digital Tools To Enhance Finance Agility

Nilly Essaides

In times of great uncertainty, one of the most effective qualities of the finance organization is agility. Agility means being able to sync up the pace of internal change with that of the external environment. Facing today’s political, economic, and financial market unpredictability, the onus is on finance to turbocharge its agility. The Hackett Group benchmarks show that top-performing agile companies are four times more likely to improve cost under volatile business conditions. They are three times more likely to make important decisions quickly, and twice as likely to respond quickly to change in business demands or conditions. In short, it pays to be agile.

Putting agility on digital “steroids”

Agility in its traditional sense is no longer enough, however. Its purpose is to help finance keep pace with external change. However, to be successful today, finance needs to be able to anticipate change and come up with contingency plans for multiple scenarios. It can accelerate its internal adaptability by adopting digital technologies. By enhancing planning techniques and processes with the powers of Big Data, advanced analytics, robotic process automation (RPA), and cloud tools, finance can spot trouble faster, predict future developments, and help companies quickly adjust course.

Here are four ways digital solutions can help:

Use sophisticated models to run multiple scenario analyses. Advanced analytics models can help finance run scenario analyses using different inputs and ask probing questions. There are too many what-ifs for the human mind to contain, especially because they are all interdependent. Using predictive models can help finance quickly run through multiple scenarios, get them to interplay, and come up with possible outcomes.

Augment finance GBS with RPA. A big part of agility is removing inefficiencies and getting the right talent doing the right things. If finance is bogged down inputting data or reconciling invoices, it won’t have a chance to help foresee events or come up with mitigation plans. New technologies like RPA are providing opportunities for quick returns that can also get around any backlash against labor arbitrage.

Leverage Big Data. Internal numerical data is not going to feed sophisticated, multidimensional models. To keep a finger on the market pulse, finance needs to start pulling real-time and leading indicator data from external sources, including social media feeds. While full Big Data capability may take time to develop, some finance organizations are already running pilot programs applying Big Data techniques to solve specific business issues.

Shift to agile planning techniques. Finally, new cloud-based, end-to-end enterprise performance management (EPM) solutions are speeding up the adoption time for EPM systems. They’re also reducing the cost of ownership, making it possible even for midsize firms to adopt dynamic planning techniques. They can then use the forecast to continuously reallocate resources to optimize returns based on shifting market realities and take a forward-looking approach to planning.

Still, finance must move even faster, to meet the increasingly risky and volatile business environment of today. The onus is on finance to take quick steps to come up the learning curve. The three most critical steps include:

  1. Create a digital strategy. Finance needs to come up with coherent strategy that’s aligned with the organization’s digital transformation objectives. If the company is looking to enhance customer experience though better utilization of social media, finance needs to define how it’s going to support its internal customers and what technologies it needs to be able to deliver on the overall strategic objective.
  1. Change the operating model. Finance needs to build the right operating model to turbocharge the agility of the function with digital technologies. It needs to pull together its best talent and place them in a centralized location to create a powerful analytics hub. A Center of Excellence can offer streamlined analytics and decision support and focus on areas where Big Data and analytics can provide real business value. It can also simplify the interaction model with business leaders and management.
  1. Train and hire new tech- and analytic-savvy professionals. Finally, finance needs to build up its digital capabilities by preparing its talent for change more quickly. Simply adopting new tools won’t get the organization to its optimal state. The skills and capabilities needed to support an uber-analytics function include intellectual curiosity, familiarity with the right technologies, and strong communication skills. Finance professionals also have to be comfortable with ambivalence: Often they will need to provide insight without 100% of the information. And they need to understand the business to be able to quickly grasp what external changes may affect the company’s performance.

Conclusion

Companies today face multiple risks and a higher level of uncertainty. Geopolitical indicators are pointing to a period of extreme unpredictability, which may lead to financial instability and both opportunities and challenges for enterprise growth. Against this backdrop, finance needs to accelerate its ability to react. It must incorporate new tools into its toolkit so it can foresee upcoming events and develop contingency plans through the adoption of new technologies like artificial intelligence, cloud-based solutions, and predictive modelling.

For more insight on financial analytics, see Become An Insight-Driven Enterprise With Predictive Finance Analytics.

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Nilly Essaides

About Nilly Essaides

Nilly Essaides is senior research director, Finance & EPM Advisory Practice at The Hackett Group. Nilly is a thought leader and frequent speaker and meeting facilitator at industry events, the author of multiple in-depth guides on financial planning & analysis topics, as well as monthly articles and numerous blogs. She was formerly director and practice lead of Financial Planning & Analysis at the Association for Financial Professionals, and managing director at the NeuGroup, where she co-led the company’s successful peer group business. Nilly also co-authored a book about knowledge management and how to transfer best practices with the American Productivity and Quality Center (APQC).

AI, Blockchain, And Cloud Fuel Banking’s Evolution

John Bertrand

Artificial intelligence (AI), blockchain, and cloud technologies are increasingly appearing on the horizon. This could be exactly what the banker ordered, given the legal mandates for open banking and General Data Protection Regulation for 2018. These three key technologies can fuel the financial services industry’s evolution into the digital age.

Artificial intelligence

AI is a collection of machine learning, natural language processing, and cognitive computing designed for scale. It is this scalability that is exciting, as it can create exponential growth and deliver today’s required personalized communications. For example, in July 2017 UK payments processed 21 million payments per business day. If 0.5% of the daily volume needed additional review, 105,000 items would need to be checked, often manually and with rules-based, tick-the-box solutions. AI would significantly increase productivity by matching payment behavior and pattern recognition, and simply asking the question, “does this look right?” AI-powered chatbots could help business users and consumers answer inquiries and enhance the customer experience.

Blockchain

Blockchain is also a mix of technologies that enables us to trust someone we do not know and protects us from cybercriminals. The block contains vital information about a party, and the chain is the sequence of third-party, verified events that have taken place over the history of the transaction. Blockchain is fully encrypted and can be permissioned for private and public groups. Given the manual, paper-based state of the supply chain, it is not surprising that we’re seeing many new proofs of concepts and pilots using blockchain.

Cloud

Cloud computing gives improved security, scale, and agility to respond to market demands and can decrease banks’ cost bases. The advances in cloud technologies permit software applications to move seamlessly between legacy, private cloud, and public cloud solutions. One such technology, containers, allows the applications to flow safely across the end-to-end processes regardless of the underlying technologies, much like how shipping containers transformed the inefficient, non-scalable 20th century transportation industry to the one today.

Finance’s digital evolution

These technologies are could be the savior of financial services industry. Financial services are rapidly becoming a technology-driven sector, evidenced by the increasing amount of money being spent in this area.

  • Financial services is now one of the largest buyers of software
  • IDC expects this figure to grow more than five percent over 2016’s spending
  • The forecast of $2.7 trillion in worldwide IT spending by 2020 is led by the financial services industry

Legacy banks and financial services firms can either build the technology themselves or work with fintechs to do so; either way it has to be done. Eminent evolutionary biologist Charles Darwin could have been discussing this new banking environment when he noted:

It is not the strongest of the species that survive, nor the most intelligent, but the one most responsive to change. 

Potential impacts of financial services’ digital evolution include:

  • Low-cost centers using AI to increase straight-through processing (STP) to 100%, thus removing cost, increasing customer satisfaction, and reducing liabilities from errors
  • Administration of trade finance through blockchain to reduce costs and increase certainty of ownership at any point in time
  • Spare computer capacity created by using the cloud, enabling banks to meet peak-day requirements and increase cybersecurity

Security is now a bottom-line concern. See The Future of Cybersecurity: Trust as Competitive Advantage.

This article was originally published on Finextra.

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Robots Are Moving Into Our Human Resources Functions

Agnes Desplechin

“When we react it will be too late,” said Elon Musk, CEO of Tesla Motors (a pioneer in the connected car market), in July at the U.S. National Governors Association Summer Meeting. The businessman expressed his concern about the development of artificial intelligence and the delay in terms of regulation that would represent “a fundamental risk to the existence of human civilization.”

Today, the thought that humans can (in some activities) be substituted by robots no longer belongs solely to fictional works such as Frankenstein (1818) or current television shows Black Mirror and Westworld.

Concerns about potential failures caused by robots are very real and present today. Even before the most advanced prototypes of robots and the possibilities offered by artificial intelligence were considered, economist John Maynard Keynes prophesied the substitution of man by machines. In “Economic Possibilities for Our Grandchildren,” published in 1930, he questioned the effects of automation on jobs, well-being, and happiness, seeking to find solutions to the issue of “technological unemployment.”

A century later, the replacement of human workers by robots is anticipated across the job spectrum. According to Laurent Alexandre, technocrat, urological surgeon, and artificial intelligence (AI) advocate, all professions will, in the near future, be threatened by AI, which will soon be everywhere. Indeed, AI it is already in your pocket; Siri and Google Assistant are early chatbots, conversational robots that will replace salesmen, attorneys, journalists, and eventually, human resource assistants.

To better understand the stakes, we must understand what AI is. Consider a machine without AI, which makes decisions based on manually defined rules. When a machine facing a large data flow learns to analyze and make decisions, intelligence is born; this is machine learning. If you’re still confused about machine learning based on this description, let’s take the example of email that you define manually as “spam” within your mailbox. Once it learns the form, structure, sender, and other details that led you to mark a message as spam (i.e., the rules you defined, even subconsciously), the machine can make the decision that a message is spam. Unlike human intelligence, the machine can be caught off guard when there are exceptions.

How AI develops is of great interest in the context of HR functions. Some examples include using automated and intelligent filters for recruitment, using robots for interviews, or having chatbots act as human resource assistants in order to answer recurring questions from employees.

AI’s contribution is often measured in terms of time and cost savings, but it can also lead to more impartiality and efficiency. Even so, the human aspects and ethics must remain the core part of the HR role. As Elon Musk suggests, we must now ensure AI retains our standards, and, crucially for the HR profession, keeps the “human” in human resources.

Will intelligent machines and HR one day walk hand in hand? AI offers prospects that are very promising and prompt many questions that will shape the evolution of our profession.

AI’s ability to end bias hinges on teaching it to play fair and constantly questioning the results.
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Diving Deep Into Digital Experiences

Kai Goerlich

 

Google Cardboard VR goggles cost US$8
By 2019, immersive solutions
will be adopted in 20% of enterprise businesses
By 2025, the market for immersive hardware and software technology could be $182 billion
In 2017, Lowe’s launched
Holoroom How To VR DIY clinics

From Dipping a Toe to Fully Immersed

The first wave of virtual reality (VR) and augmented reality (AR) is here,

using smartphones, glasses, and goggles to place us in the middle of 360-degree digital environments or overlay digital artifacts on the physical world. Prototypes, pilot projects, and first movers have already emerged:

  • Guiding warehouse pickers, cargo loaders, and truck drivers with AR
  • Overlaying constantly updated blueprints, measurements, and other construction data on building sites in real time with AR
  • Building 3D machine prototypes in VR for virtual testing and maintenance planning
  • Exhibiting new appliances and fixtures in a VR mockup of the customer’s home
  • Teaching medicine with AR tools that overlay diagnostics and instructions on patients’ bodies

A Vast Sea of Possibilities

Immersive technologies leapt forward in spring 2017 with the introduction of three new products:

  • Nvidia’s Project Holodeck, which generates shared photorealistic VR environments
  • A cloud-based platform for industrial AR from Lenovo New Vision AR and Wikitude
  • A workspace and headset from Meta that lets users use their hands to interact with AR artifacts

The Truly Digital Workplace

New immersive experiences won’t simply be new tools for existing tasks. They promise to create entirely new ways of working.

VR avatars that look and sound like their owners will soon be able to meet in realistic virtual meeting spaces without requiring users to leave their desks or even their homes. With enough computing power and a smart-enough AI, we could soon let VR avatars act as our proxies while we’re doing other things—and (theoretically) do it well enough that no one can tell the difference.

We’ll need a way to signal when an avatar is being human driven in real time, when it’s on autopilot, and when it’s owned by a bot.


What Is Immersion?

A completely immersive experience that’s indistinguishable from real life is impossible given the current constraints on power, throughput, and battery life.

To make current digital experiences more convincing, we’ll need interactive sensors in objects and materials, more powerful infrastructure to create realistic images, and smarter interfaces to interpret and interact with data.

When everything around us is intelligent and interactive, every environment could have an AR overlay or VR presence, with use cases ranging from gaming to firefighting.

We could see a backlash touting the superiority of the unmediated physical world—but multisensory immersive experiences that we can navigate in 360-degree space will change what we consider “real.”


Download the executive brief Diving Deep Into Digital Experiences.


Read the full article Swimming in the Immersive Digital Experience.

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Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Chief Futurist at SAP Innovation Center network His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation. Share your thoughts with Kai on Twitter @KaiGoe.heif Futu

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Jenny Dearborn: Soft Skills Will Be Essential for Future Careers

Jenny Dearborn

The Japanese culture has always shown a special reverence for its elderly. That’s why, in 1963, the government began a tradition of giving a silver dish, called a sakazuki, to each citizen who reached the age of 100 by Keiro no Hi (Respect for the Elders Day), which is celebrated on the third Monday of each September.

That first year, there were 153 recipients, according to The Japan Times. By 2016, the number had swelled to more than 65,000, and the dishes cost the already cash-strapped government more than US$2 million, Business Insider reports. Despite the country’s continued devotion to its seniors, the article continues, the government felt obliged to downgrade the finish of the dishes to silver plating to save money.

What tends to get lost in discussions about automation taking over jobs and Millennials taking over the workplace is the impact of increased longevity. In the future, people will need to be in the workforce much longer than they are today. Half of the people born in Japan today, for example, are predicted to live to 107, making their ancestors seem fragile, according to Lynda Gratton and Andrew Scott, professors at the London Business School and authors of The 100-Year Life: Living and Working in an Age of Longevity.

The End of the Three-Stage Career

Assuming that advances in healthcare continue, future generations in wealthier societies could be looking at careers lasting 65 or more years, rather than at the roughly 40 years for today’s 70-year-olds, write Gratton and Scott. The three-stage model of employment that dominates the global economy today—education, work, and retirement—will be blown out of the water.

It will be replaced by a new model in which people continually learn new skills and shed old ones. Consider that today’s most in-demand occupations and specialties did not exist 10 years ago, according to The Future of Jobs, a report from the World Economic Forum.

And the pace of change is only going to accelerate. Sixty-five percent of children entering primary school today will ultimately end up working in jobs that don’t yet exist, the report notes.

Our current educational systems are not equipped to cope with this degree of change. For example, roughly half of the subject knowledge acquired during the first year of a four-year technical degree, such as computer science, is outdated by the time students graduate, the report continues.

Skills That Transcend the Job Market

Instead of treating post-secondary education as a jumping-off point for a specific career path, we may see a switch to a shorter school career that focuses more on skills that transcend a constantly shifting job market. Today, some of these skills, such as complex problem solving and critical thinking, are taught mostly in the context of broader disciplines, such as math or the humanities.

Other competencies that will become critically important in the future are currently treated as if they come naturally or over time with maturity or experience. We receive little, if any, formal training, for example, in creativity and innovation, empathy, emotional intelligence, cross-cultural awareness, persuasion, active listening, and acceptance of change. (No wonder the self-help marketplace continues to thrive!)

The three-stage model of employment that dominates the global economy today—education, work, and retirement—will be blown out of the water.

These skills, which today are heaped together under the dismissive “soft” rubric, are going to harden up to become indispensable. They will become more important, thanks to artificial intelligence and machine learning, which will usher in an era of infinite information, rendering the concept of an expert in most of today’s job disciplines a quaint relic. As our ability to know more than those around us decreases, our need to be able to collaborate well (with both humans and machines) will help define our success in the future.

Individuals and organizations alike will have to learn how to become more flexible and ready to give up set-in-stone ideas about how businesses and careers are supposed to operate. Given the rapid advances in knowledge and attendant skills that the future will bring, we must be willing to say, repeatedly, that whatever we’ve learned to that point doesn’t apply anymore.

Careers will become more like life itself: a series of unpredictable, fluid experiences rather than a tightly scripted narrative. We need to think about the way forward and be more willing to accept change at the individual and organizational levels.

Rethink Employee Training

One way that organizations can help employees manage this shift is by rethinking training. Today, overworked and overwhelmed employees devote just 1% of their workweek to learning, according to a study by consultancy Bersin by Deloitte. Meanwhile, top business leaders such as Bill Gates and Nike founder Phil Knight spend about five hours a week reading, thinking, and experimenting, according to an article in Inc. magazine.

If organizations are to avoid high turnover costs in a world where the need for new skills is shifting constantly, they must give employees more time for learning and make training courses more relevant to the future needs of organizations and individuals, not just to their current needs.

The amount of learning required will vary by role. That’s why at SAP we’re creating learning personas for specific roles in the company and determining how many hours will be required for each. We’re also dividing up training hours into distinct topics:

  • Law: 10%. This is training required by law, such as training to prevent sexual harassment in the workplace.

  • Company: 20%. Company training includes internal policies and systems.

  • Business: 30%. Employees learn skills required for their current roles in their business units.

  • Future: 40%. This is internal, external, and employee-driven training to close critical skill gaps for jobs of the future.

In the future, we will always need to learn, grow, read, seek out knowledge and truth, and better ourselves with new skills. With the support of employers and educators, we will transform our hardwired fear of change into excitement for change.

We must be able to say to ourselves, “I’m excited to learn something new that I never thought I could do or that never seemed possible before.” D!

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