Why You Need To Rethink The Way Your Business Operates

Simon Dale

The pace of change in business today is staggering. As expectations for quality user experiences rise ever higher, this need for speed is driving enterprises to embark on digital transformation.

Rising expectations

You could call it life imitating art, but customers’ online behavior is now setting sky-high expectations for real-world encounters. Customers demand a single, consistent experience across every touch point.

Everyone has access to multiple channels, which puts pressure on companies to provide an integrated experience. You just can’t deliver a slick experience on a mobile device in isolation. You can’t expect your customers to be happy with one great experience that doesn’t extend beyond the confines of their mobile screens.

But it’s not just about meeting customer expectations. Inside the enterprise, employees are leading the charge. They want to collaborate with their coworkers in the same way as they can with friends. At work, you expect the same powerful technology that you use at home.

Yet on the customer experience side, many of the executives I speak with in manufacturing, retail, services, life sciences, and other sectors are still struggling to create the perfect cross-channel experiences for their customers. Many organizations persist with clunky apps even though they’re a serious drag on productivity.

We are all technology companies

These days, all successful companies are technology companies that just happen to produce other things as well. So it doesn’t matter whether you’re selling beauty products, manufacturing industrial cement, or educating young minds, the market and people have changed.

Adopting digital technologies is crucial if you want to meet modern expectations. You need to take advantage of digital tools and technology to provide customers with what they want in a targeted, effective, and seamless way.

Getting ahead in the digital journey

While large traditional companies—with decades of history and legacy—are very different from nimble digital entrants, clearly only those organizations that take advantage of an always-on, digitally connected and Big Data-driven world can hope to succeed.

Cloud and mobile computing combined with endless streams of data have created the potential to transform nearly everything.

For established organizations there’s an urgent need to rewire your end-to-end business processes for the digital world. You need to modernize core systems to support new kinds of digital interactions.

Accumulating and analyzing more valid data

Take the case of a long-established cement producer based in Thailand. While Siam City Cement is not an obvious early candidate for digital transformation, its needs were compelling. Digital transformation is now well underway in its business as the company strives to respond to changing consumer behavior.

For Siam City, the only way to keep up with customer demand was to understand customer data better. Using a next-generation ERP business suite as its digital core, it now has critical information available in real time, helping the company make decisions quickly and ensure it is offering customers the best products and services possible. The organization has also cut month-end closing in half.

In pursuit of excellence

Over in Australia, Melbourne’s La Trobe University went from having a fragmented finance system with over 15 years of customizations to an ERP-based finance solution in under 20 weeks.

By simplifying its entire IT landscape and architecture, the university’s financial process is now much faster. Access to real-time data is leading to swifter decision making. By comparison, under the old finance system, 72 customized reports were produced each month. Now, there are just five. This has eliminated an entire day of work from the university’s finance administration team, freeing them up to focus on more useful projects.

But more than this, with reliable financial data, the university can now make informed decisions on which programs to increase or which facilities to enhance.

Pioneering a new beauty category

And for the Korean beauty products startup Memebox, within six months of going live with an ERP-based finance solution, the company saw a dramatic uptick in sales productivity.

These efficiencies stem from improved inventory accuracy. With real-time tracking, Memebox has reduced product delivery lead times, so customers are receiving the right products more quickly while revenue for Memebox continues to grow.

Customer experience is the heart of digital transformation

These days, attracting, winning, and retaining customers requires personalized cross-channel interactions and individualization of products and services. Organizations that embrace digital technologies and modernize their end-to-end processes will place themselves in the strongest position to succeed.

Read more SAP S/4HANA success stories and follow me at @SimonDWork to stay on top of the latest developments.

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Simon Dale

About Simon Dale

Simon Dale has the responsibility at SAP Asia Pacific and Japan to establish and scale the business for SAP S/4HANA, the next-generation business suite from SAP. His portfolio encompasses both the traditional on-premise solution go-to-market strategy, as well as the latest cloud solutions. Prior to this role, Simon launched and ran SAP’s managed service for SAP solutions, SAP HANA Enterprise Cloud, in Asia. A veteran of 25 years in the IT industry, Simon sits on the advisory boards of both the Singapore Management University of Information Systems as well as the Nanyang Polytechnic School of IT. Simon is an occasional angel investor in startups and committed to active mentoring and coaching, especially to early talent and women in IT.

Analytics Leaders In Finance Have Higher Profitability

Tom Groenfeldt

The phrase “Big Data is the new oil,” is looking more than a little shopworn. Most organizations have far more data than they know how to use, write Tom Davenport and Jeanne G. Harris in the recently reissued and updated book Competing on Analytics – the New Science of Winning.

”The data in their systems is like the box of photos you keep in your attic, waiting for the ‘someday’ when you impose meaning on the chaos. IDC estimates that only 0.5% of data is ever analyzed, and we would guess that the amount of data is growing faster than the amount of it that’s analyzed.”

The International Institute for Analytics, co-founded by Davenport, conducted a survey in 2016 of 50 companies across several industries and found that few were analytical competitors. Amazon, no surprise, had the highest score, and financial services firms were the second most analytical industry, but on average banks were not at the analytical competitor level. The lowest ranked industries were healthcare and health insurance.

The top ranked had four key characteristics:

  • They supported a strategic capability
  • Their approach was enterprise-wide
  • The senior management team was committed
  • The company made a significant strategic bet on analytics-based competition

Some of the names in finance will not be a surprise. Progressive Insurance and Capital One have been leaders in using credit scores to improve profits. Progressive was early to understand that people with good credit scores also had better driving records than people with poor credit. But then Progressive, like Capital One, began picking apart those same FICO credit scores looking for potential customers who were better risks than their scores indicated, picking up profitable business that competitors couldn’t recognize.

Central control and standardization

Analytical leaders don’t leave data and analytics to departments; they hold it centrally or impose uniform standards for how it is gathered, stored, and used.

RBC Financial Group decided in the 1970s that customer data would be owned by the enterprise and held centrally. Bank of America decided that interest rate exposure would be managed in a consistent way across the bank.

That emphasis on an enterprise-wide approach is fundamental to competing on analytics because departmental analytics tend to rely on Excel. User-generated spreadsheets often have errors, and by their nature create multiple versions of the truth. When business users meet and bring their own spreadsheets, discussions often get bogged down in whose data is accurate. Analytics programs often have to overcome fiefdoms within the organization, the authors write.

Firms that get it right see significant profits. Kroger uses the customer analytics tool Dunnhumby, which was so useful to the British grocer Tesco that it bought the company. Kroger grew its same-store sales for 52 straight quarters through its customer loyalty program and made millions selling shopping data to food companies. It should be interesting to see what happens as Kroger meets Amazon and Whole Foods.

Capital One saw earnings per share and return on equity grow 20% year on year through its aggressive analytics. The bank runs about 80,000 marketing experiments per year. It increased retention in its savings business by 87% and lowered the cost of acquiring by 83%.

The authors quote Bain, which said that really good analytics companies are twice as likely to be in the top quartile, three times as likely to execute decisions as expected, and five times as likely to make decisions faster.

Commitment to long-term effectiveness

The leaders are not standing still. The CIO of Capital One looks forward to using machine learning to provide more tailored products for customers. Credit Suisse is using Quill from Narrative Science to produce investment research reports on 5,000 companies it covers.

Becoming analytical takes time and sustained commitment. The authors say it can take 18 to 36 months of working with data to get into the practice, and sometimes the process slips. They recount a conversation with a banker whose firm used to be a leader in analytics, but now said the organization was slipping into silos of data. That can lead to unfortunate cases like one where a customer with a $100 million trust account was charged $35 for a bounced check. A manager, who apparently couldn’t see the trust account, said the customer’s savings account wasn’t large enough to justify waiving the fee.

Analytics is easier at digital corporations like eBay or Netflix than at “a legacy corporation where IT appears to have been built in a series of weekend handyman jobs,” they note.

For more on trends shaping the future of finance, read The Digitalist’s Transformation Ahead Series.

This article originally appeared on Financial Technology.

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Tom Groenfeldt

About Tom Groenfeldt

Tom Groenfeldt is a freelance reporter who focuses largely on finance and technology including trading, risk, back-office systems, big data, analytics, retail banking, international banking, and e-commerce. His work appears in several publications, including Forbes.com in the U.S. and Banking Technology in London. In 2015, he was named to the “FinServ 25,” the top 25 top global influencers in banking, by The Financial Brand.

Transformation Ahead, Part 3: 10 Trends Shaping The Future Of Finance

Randy Garrison

Part 3 of the of the 4-part “Transformation Ahead” series

As I wrote in my previous blogs in this series, 10 key trends are significantly changing the future of finance. To ensure that their finance organizations keep pace with the change demanded by the business and catalyzed by disruptive technologies, CFOs must be prepared to address these trends.

Trend 5. Finance will become the analytics hub of the organization.

Successful finance organizations are focusing on enterprise-level analytics and key performance indicators, not just information related to the finance function. To support this shift, the finance organization will need to develop a deep understanding of the business and the ability to translate this knowledge into financial and operational metrics.

Day-to-day analytics should provide self-service for business users. With artificial intelligence and natural language processing making analytics tools more intuitive for users, the finance organization can step away from being analytics experts and instead focus on becoming strategic partners to the business. Finance experts can help the business interpret analytics and discover trends, opportunities, or the root cause of issues. With the use of predictive algorithms, finance organizations can help shape strategy by performing what-if comparisons across multiple scenarios.

Trend 6. Core finance processes will become dynamic, continuous processes.

Too slow to support real-time digital businesses, traditional processes that focus on month-end close and annual budget cycles must be replaced. Instead, accounting is evolving into a continuous activity, performed primarily through automation and business networks. In this environment, closing the books will be just another task – not a cause for stress or overtime.

Other than external reporting for quarterly or annual results, the close will no longer be needed to support financial performance evaluation for the business. Budgeting will also become a dynamic activity, one that supports rapid adjustments to meet changing business requirements. For more on this topic, read the Continuous Accounting Series in the Digitalist.

Trend 7. Finance will be viewed as a business value creator.

As automation and trends such as AI, machine learning, and networking reduce the manual effort required for transactional functions, CFOs will be able to add more top- and bottom-line value by focusing more effort on complex topics such as transfer pricing optimization, proactive working capital management, tax optimization, and proactive currency and commodity hedge management. Detailed, timely insights will equip the finance organization to create data-driven value for the business.

My next blog will conclude with a look at three more significant trends – and my recommendations for how to get ready and take charge. You can read more about finance solutions at www.sap.com/cfo.

Follow SAP Finance online: @SAPFinance (Twitter)  | LinkedIn | FacebookYouTube

 

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Randy Garrison

About Randy Garrison

Randy Garrison is vice president, Global Line of Business Finance and Head of Value Advisory at SAP. The LoB Finance organization is responsible for the full suite of SAP solutions for the Office of the CFO.

Randy has held several roles at SAP, most recently in leadership within SAP’s Services business. In these roles, he has led both large and small teams focused on analytics strategy, data strategy, business transformation, Big Data, and so on, focused on the implementation, adoption, and value realization of SAP’s products.

Randy is a Certified Public Accountant, Certified Management Accountant, Chartered Global Management Accountant, and a member of the AICPA and the Institute of Management Accountants.

He is married with five children ranging in age from 32 to 7 years old. Personal interests include golf, hot air ballooning, anything the kids do.

Human Skills for the Digital Future

Dan Wellers and Kai Goerlich

Technology Evolves.
So Must We.


Technology replacing human effort is as old as the first stone axe, and so is the disruption it creates.
Thanks to deep learning and other advances in AI, machine learning is catching up to the human mind faster than expected.
How do we maintain our value in a world in which AI can perform many high-value tasks?


Uniquely Human Abilities

AI is excellent at automating routine knowledge work and generating new insights from existing data — but humans know what they don’t know.

We’re driven to explore, try new and risky things, and make a difference.
 
 
 
We deduce the existence of information we don’t yet know about.
 
 
 
We imagine radical new business models, products, and opportunities.
 
 
 
We have creativity, imagination, humor, ethics, persistence, and critical thinking.


There’s Nothing Soft About “Soft Skills”

To stay ahead of AI in an increasingly automated world, we need to start cultivating our most human abilities on a societal level. There’s nothing soft about these skills, and we can’t afford to leave them to chance.

We must revamp how and what we teach to nurture the critical skills of passion, curiosity, imagination, creativity, critical thinking, and persistence. In the era of AI, no one will be able to thrive without these abilities, and most people will need help acquiring and improving them.

Anything artificial intelligence does has to fit into a human-centered value system that takes our unique abilities into account. While we help AI get more powerful, we need to get better at being human.


Download the executive brief Human Skills for the Digital Future.


Read the full article The Human Factor in an AI Future.


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Dan Wellers

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

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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The Human Factor In An AI Future

Dan Wellers and Kai Goerlich

As artificial intelligence becomes more sophisticated and its ability to perform human tasks accelerates exponentially, we’re finally seeing some attempts to wrestle with what that means, not just for business, but for humanity as a whole.

From the first stone ax to the printing press to the latest ERP solution, technology that reduces or even eliminates physical and mental effort is as old as the human race itself. However, that doesn’t make each step forward any less uncomfortable for the people whose work is directly affected – and the rise of AI is qualitatively different from past developments.

Until now, we developed technology to handle specific routine tasks. A human needed to break down complex processes into their component tasks, determine how to automate each of those tasks, and finally create and refine the automation process. AI is different. Because AI can evaluate, select, act, and learn from its actions, it can be independent and self-sustaining.

Some people, like investor/inventor Elon Musk and Alibaba founder and chairman Jack Ma, are focusing intently on how AI will impact the labor market. It’s going to do far more than eliminate repetitive manual jobs like warehouse picking. Any job that involves routine problem-solving within existing structures, processes, and knowledge is ripe for handing over to a machine. Indeed, jobs like customer service, travel planning, medical diagnostics, stock trading, real estate, and even clothing design are already increasingly automated.

As for more complex problem-solving, we used to think it would take computers decades or even centuries to catch up to the nimble human mind, but we underestimated the exponential explosion of deep learning. IBM’s Watson trounced past Jeopardy champions in 2011 – and just last year, Google’s DeepMind AI beat the reigning European champion at Go, a game once thought too complex for even the most sophisticated computer.

Where does AI leave human?

This raises an urgent question for the future: How do human beings maintain our economic value in a world in which AI will keep getting better than us at more and more things?

The concept of the technological singularity – the point at which machines attain superhuman intelligence and permanently outpace the human mind – is based on the idea that human thinking can’t evolve fast enough to keep up with technology. However, the limits of human performance have yet to be found. It’s possible that people are only at risk of lagging behind machines because nothing has forced us to test ourselves at scale.

Other than a handful of notable individual thinkers, scientists, and artists, most of humanity has met survival-level needs through mostly repetitive tasks. Most people don’t have the time or energy for higher-level activities. But as the human race faces the unique challenge of imminent obsolescence, we need to think of those activities not as luxuries, but as necessities. As technology replaces our traditional economic value, the economic system may stop attaching value to us entirely unless we determine the unique value humanity offers – and what we can and must do to cultivate the uniquely human skills that deliver that value.

Honing the human advantage

As a species, humans are driven to push past boundaries, to try new things, to build something worthwhile, and to make a difference. We have strong instincts to explore and enjoy novelty and risk – but according to psychologist Mihaly Csikszentmihalyi, these instincts crumble if we don’t cultivate them.

AI is brilliant at automating routine knowledge work and generating new insights from existing data. What it can’t do is deduce the existence, or even the possibility, of information it isn’t already aware of. It can’t imagine radical new products and business models. Or ask previously unconceptualized questions. Or envision unimagined opportunities and achievements. AI doesn’t even have common sense! As theoretical physicist Michio Kaku says, a robot doesn’t know that water is wet or that strings can pull but not push. Nor can robots engage in what Kaku calls “intellectual capitalism” – activities that involve creativity, imagination, leadership, analysis, humor, and original thought.

At the moment, though, we don’t generally value these so-called “soft skills” enough to prioritize them. We expect people to develop their competency in emotional intelligence, cross-cultural awareness, curiosity, critical thinking, and persistence organically, as if these skills simply emerge on their own given enough time. But there’s nothing soft about these skills, and we can’t afford to leave them to chance.

Lessons in being human

To stay ahead of AI in an increasingly automated world, we need to start cultivating our most human abilities on a societal level – and to do so not just as soon as possible, but as early as possible.

Singularity University chairman Peter Diamandis, for example, advocates revamping the elementary school curriculum to nurture the critical skills of passion, curiosity, imagination, critical thinking, and persistence. He envisions a curriculum that, among other things, teaches kids to communicate, ask questions, solve problems with creativity, empathy, and ethics, and accept failure as an opportunity to try again. These concepts aren’t necessarily new – Waldorf and Montessori schools have been encouraging similar approaches for decades – but increasing automation and digitization make them newly relevant and urgent.

The Mastery Transcript Consortium is approaching the same problem from the opposite side, by starting with outcomes. This organization is pushing to redesign the secondary school transcript to better reflect whether and how high school students are acquiring the necessary combination of creative, critical, and analytical abilities. By measuring student achievement in a more nuanced way than through letter grades and test scores, the consortium’s approach would inherently require schools to reverse-engineer their curricula to emphasize those abilities.

Most critically, this isn’t simply a concern of high-tuition private schools and “good school districts” intended to create tomorrow’s executives and high-level knowledge workers. One critical aspect of the challenge we face is the assumption that the vast majority of people are inevitably destined for lives that don’t require creativity or critical thinking – that either they will somehow be able to thrive anyway or their inability to thrive isn’t a cause for concern. In the era of AI, no one will be able to thrive without these abilities, which means that everyone will need help acquiring them. For humanitarian, political, and economic reasons, we cannot just write off a large percentage of the population as disposable.

In the end, anything an AI does has to fit into a human-centered value system that takes our unique human abilities into account. Why would we want to give up our humanity in favor of letting machines determine whether or not an action or idea is valuable? Instead, while we let artificial intelligence get better at being what it is, we need to get better at being human. That’s how we’ll keep coming up with groundbreaking new ideas like jazz music, graphic novels, self-driving cars, blockchain, machine learning – and AI itself.

Read the executive brief Human Skills for the Digital Future.

Build an intelligent enterprise with AI and machine learning to unite human expertise and computer insights. Run live with SAP Leonardo.


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Dan Wellers

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

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