Why CFOs Must Become Digitally Savvy

Nilly Essaides

Digital transformation is all around us. New technologies are revolutionizing how companies do business and engage with customers. They are also changing the way finance delivers services to its internal customers. Out are paper invoices; in are e-invoicing portals. Out are legacy on-premise applications; in are cloud-based applications. Out is manual reconciliation; in is robotic process automation (RPA). Big Data and advanced analytics are giving finance the power to support better business decisions about investment opportunities, cost savings, and new sources of revenue.

Cases in point

  • At one telecom company, finance uses Big Data discovery and predictive analytics technology to help solve business problems. Finance set out to find out what kind of products customers in a particular area were looking for. Using Big Data and advanced analytics, the finance team came up with answers that help the business decide what to keep in inventory, increasing sales and reducing cost.
  • A medical device company decided to overhaul its order-entry process by using RPA. The company needed a comprehensive automation platform that was flexible and accurate, provided a strict control environment, and could be easily and quickly deployed. It took 6 months to deploy 14 robots and completely change the processes and significantly redeploy headcount. This approach also improved accuracy, which, among other benefits, helps get cash in the door faster.
  • At another company, an innovative cloud planning tool created a newly collaborative environment with self-service capabilities so that business units contribute directly to the forecasting and budgeting process. The new technology sped up the process while also improving data integrity.
  • Finally, at one global company, artificial intelligence (AI) is helping finance improve its forecasting accuracy by pulling in third-party data based on social media conversations from all over the world. The third-party provider relies on AI to gauge the intensity of the conversation to predict social and political events that may lead to market disruptions.

Many finance organizations still lag in achieving the full potential of digital technologies. Our 2017 key issues study shows that finance executives almost universally expect digital transformation to have a significant impact on their performance and service-delivery model. But they rank their current execution capabilities as low. They’re also not taking big steps to correct this mismatch.

How to become a digitally savvy CFO

That’s why CFOs need to become digitally savvy. Their primary goal is to close the gap between the development and execution of a digital strategy for the finance function. The digitally savvy CFO is the evangelist and steward of the effort to bring new technologies and a digital vision to the finance team. This way, the enterprise can benefit from the premise of more technologically enabled processes, advanced analytics, and self-service solutions.

Here are steps the CFO can take to move the finance function to the digital era:

  1. Build a customer-centric digital process: CFOs must focus finance on serving internal customers more efficiently and effectively. This may involve streamlining repetitive processes by moving them to a global business services organization. Or it might involve using tools like RPA to automate parts of the process that are rule-based and can be handed off to algorithm-driven technologies, freeing up staff time to focus on more value-added tasks.
  1. Build a digital architecture: Finance should create a connected and agile technology platform that integrates multiple applications to connect vendors/suppliers, end customers, and internal customers. This platform should be able to leverage a variety of internal, external, structured, and unstructured data.
  1. Develop digital competency through centers of excellence (CoEs). CFOs should establish digital CoEs where technologies like RPA can be tested to discover applications with strong business cases for deployment in the finance function. The CoEs act as “virtual sandboxes” in which new technologies can be tried out on a small scale.
  1. Create digital value through data governance: CFOs should spearhead data governance efforts to make sure enterprise data is accurate and ready to be used. Master data management (MDM), which defines the way data is stored and managed, is an increasingly important area of focus. Without it, analytics applications cannot run effectively.
  1. Develop data “smarts:” Data is of no value unless it’s used to drive action. Going digital means merging data with sophisticated analytics that provide insight into what is going to happen and what to do about it. Finance must deliver the right information at the right time to the right people so the business can take action.
  1. Develop a digital workforce: Finally, digitally savvy CFOs must come up with a talent development strategy designed to support their emerging approach. A full 80% of participants in our key issues study believe that digitization will change the skills and leadership approach required to manage their function. But the study also found that very few finance organizations plan major updates to talent management programs and practices this year. Finance will have to take bolder steps if it is to retrain and reshape its workforce to become more strategic in nature, collaborate with the business, and provide higher-level analytics support.

CFOs must stay vigilant regarding new digital technologies, continuously educating themselves and encouraging their staff to do the same. They must keep abreast of what other companies are doing, learning about potential use cases that may hold promise for their own activities and educating other company leaders on these topics. Most important, they must make it clear that they are fully committed to digital transformation by assigning these projects the highest priority and rewarding staff for implementing new technologies and mastering new skills.

For more digital transformation strategies, see Your Digital Transformation Journey Begins Here.

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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).

Machine Learning: The Next Evolution Of Automation And Accuracy For Finance

Peter David

The role of finance is in a constant state of metamorphosis, shedding traditional fiduciary control and compliance to form strategic partnerships and spread its wings as an indomitable catalyst for business growth. However, many day-to-day activities still require considerable manual intervention, which is hampering the full benefit of any digital strategy.

For years, CFOs have invested in various technologies to maximize the potential of their entire organization. Analytics – historical, real-time, Big Data, and predictive – are connecting operations, functions, and individuals to provide full visibility and access to insights. Then, more recently, blockchain and the Internet of Things have come on the scene, enabling sophisticated data collection and analysis to deliver actionable insights that can help build a competitive advantage.

Now, CFOs are considering the promise of intelligent automation through machine learning. Instead of just capturing and reporting data, computers can “think,” make better decisions, and research faster by creating mathematical algorithms based on accumulated data. But are finance organizations ready to fully trust that these automated systems are operating alone with the right information?

The journey to digital maturity builds the foundation for trusted data

Data accuracy is one of many topics associated with an abundance of clichés and shareable quotes from various experts. Personally, I believe Aaron Koblin, an entrepreneur best known for his innovative use of data visualization, crowdsourcing, virtual reality, and interactive film, concisely summed up the current state of data: “I think you can have a ridiculously enormous and complex data set, but if you have the right tools and methodology, then it’s not a problem.”

Every step taken along the evolutionary trail of finance organizations has played some part in setting the stage for greater automation with improved data accuracy. No matter how small or large the digital investment, organizations are moving closer to gaining trust in the accuracy of automated data analysis, while processes accelerate and require less human interaction.

Take, for example, blockchain. Companies are finding value in this technology, beyond bitcoin, to monitor and manage resources at the enterprise and local level, leverage validated information, and deliver better insights on how to maintain compliance, seize new opportunities, and deflect risk. Companies then gain the right methods, powered by in-memory computing, to gain better visibility into operational performance and leverage Big Data to make insight-driven decisions.

Machine learning is the next logical step to use this enriched, validated, and accurate data to liberate finance professionals from at least five kinds of redundant, low-value – yet necessary – work.

1. Digital business assistants

Voice-activated intelligent assistants, based on machine learning technology, will understand the business context of processes in different areas. These digital assistants can create a holistic view of a specific business situation providing, for example, an overview of customer status. Finance experts can then analyze the information and make proposals to optimally handle a particular situation. They gain transparency into the situation instantly, equipping them with the insight needed to make the best decisions without investing time to research.

2. Financial planning and analysis

Machine learning capabilities, built into predictive analytics, go far beyond pure analysis of existing data. Based on various data sources, the functionality identifies trends, predicts impacts on your business numbers, and determines a view into the future of your business with intelligent projections and what-if analysis. This enables finance professionals to make better decisions for a brighter future for the business. The resulting capability is a clear driver for elevating the office of the CFO as a valuable partner of the business and a strategic advisor to the CEO.

3. Finance operations

Most finance operations still rely heavily on manual, time-consuming activities. Consequently, digital technology offers vast potential to increase automation and focus more on exception-handling and service quality. Take, for example, a receivables management process where incoming payments need to be matched with invoices. Thanks to pooling, discounts, and other factors, matching becomes anything but trivial. With machine learning, matching rates are not only better, but also improve over time by learning from the data and human-exception decisions.

The next step is to add the remittance advice extractor. In turn, matching rates increase because machine learning extracts information from unstructured advice and translates them into structured data, which automates the clearing process. Financial service customer requests are then highly automated, unstructured requests are analyzed, context is identified, and answers are proposed to the service agent or proactively addressed. With this task automated, agents are freed up to focus on critical special requests.

4. Enterprise governance, risk, and compliance

Machine learning helps detect and prevent fraud by identifying and ranking information that positively correlates with defined attributes of duplicitous activities. Investigators learn from their company’s history to detect new fraud patterns and reduce false positives. These predictive detection methods can be incorporated into existing methods and fraud management strategies.

It’s time to embrace machine learning as part of continuous data innovation

Increasingly, CFOs are acknowledging that the digital transformation of finance is an essential, urgent, and ongoing task. In fact, the Oxford Economics study, “How Finance Leadership Pays Off,” sponsored by SAP, revealed that 73% of surveyed finance leaders believe that automation is improving their function’s efficiency and giving employees more bandwidth for value-added tasks.

Recognizing the importance of such an evolution does not always – or automatically – open the door to the need for more resources. Through machine learning, finance organization can do more than ever before with lower or current support levels, innovate new ways to work, and increase efficiency, output, and, ultimately, profitability.

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

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Peter David

About Peter David

Peter David has been regional chief financial officer of Europe Middle East and Africa at SAP since December 2014 and served as its chief financial officer of Latin America and The Caribbean from September 2012 to July 2013. Mr. David established a strategic direction and oversees its financial and operational activities region-wide. He joined SAP in 1995 and served as its chief financial officer and chief operating officer in the past.

Digitalist Flash Briefing: Machine Learning: Futuristic Sci-Fi Or Business-Critical Now? (Part 2)

Bonnie D. Graham

Reality check! Machine learning and the world of artificial intelligence (AI) are no longer the stuff of science fiction. They’re here – now – and many businesses and industries are taking advantage.

  • Amazon Echo or Dot: Enable the “Digitalist” flash briefing skill, and ask Alexa to “play my flash briefings” on every business day.
  • Alexa on a mobile device:
    • Download the Amazon Alexa app: Select Skills, and search “Digitalist”. Then, select Digitalist, and click on the Enable button.
    • Download the Amazon app: Click on the microphone icon and say “Play my flash briefing.”

Find and listen to previous Flash Briefings on Digitalistmag.com.

Read more on today’s topic

 

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Bonnie D. Graham

About Bonnie D. Graham

Bonnie D. Graham is the creator, producer and host/moderator of 29 Game-Changers Radio series presented by SAP, bringing technology and business strategy thought leadership panel discussions to a global audience via the Business Channel on World Talk Radio. A broadcast journalist with nearly 20 years in media production and hosting, Bonnie has held marketing communications management roles in the business software, financial services, and real estate industries. She calls SAP Radio her "dream job". Listen to Coffee Break with Game-Changers.

The Future Will Be Co-Created

Dan Wellers and Timo Elliott

 

Just 3% of companies have completed enterprise digital transformation projects.
92% of those companies have significantly improved or transformed customer engagement.
81% of business executives say platforms will reshape industries into interconnected ecosystems.
More than half of large enterprises (80% of the Global 500) will join industry platforms by 2018.

Link to Sources


Redefining Customer Experience

Many business leaders think of the customer journey or experience as the interaction an individual or business has with their firm.

But the business value of the future will exist in the much broader, end-to-end experiences of a customer—the experience of travel, for example, or healthcare management or mobility. Individual companies alone, even with their existing supplier networks, lack the capacity to transform these comprehensive experiences.


A Network Effect

Rather than go it alone, companies will develop deep collaborative relationships across industries—even with their customers—to create powerful ecosystems that multiply the breadth and depth of the products, services, and experiences they can deliver. Digital native companies like Baidu and Uber have embraced ecosystem thinking from their early days. But forward-looking legacy companies are beginning to take the approach.

Solutions could include:

  • Packaging provider Weig has integrated partners into production with customers co-inventing custom materials.
  • China’s Ping An insurance company is aggressively expanding beyond its sector with a digital platform to help customers manage their healthcare experience.
  • British roadside assistance provider RAC is delivering a predictive breakdown service for drivers by acquiring and partnering with high-tech companies.

What Color Is Your Ecosystem?

Abandoning long-held notions of business value creation in favor of an ecosystem approach requires new tactics and strategies. Companies can:

1.  Dispassionately map the end-to-end customer experience, including those pieces outside company control.

2.  Employ future planning tactics, such as scenario planning, to examine how that experience might evolve.

3.  Identify organizations in that experience ecosystem with whom you might co-innovate.

4.  Embrace technologies that foster secure collaboration and joint innovation around delivery of experiences, such as cloud computing, APIs, and micro-services.

5.  Hire, train for, and reward creativity, innovation, and customer-centricity.


Evolve or Be Commoditized

Some companies will remain in their traditional industry boxes, churning out products and services in isolation. But they will be commodity players reaping commensurate returns. Companies that want to remain competitive will seek out their new ecosystem or get left out in the cold.


Download the executive brief The Future Will be Co-Created.


Read the full article The Future Belongs to Industry-Busting Ecosystems.

Turn insight into action, make better decisions, and transform your business.  Learn how.

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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.

About Timo Elliott

Timo Elliott is an Innovation Evangelist for SAP and a passionate advocate of innovation, digital business, analytics, and artificial intelligence. He was the eighth employee of BusinessObjects and for the last 25 years he has worked closely with SAP customers around the world on new technology directions and their impact on real-world organizations. His articles have appeared in articles such as Harvard Business Review, Forbes, ZDNet, The Guardian, and Digitalist Magazine. He has worked in the UK, Hong Kong, New Zealand, and Silicon Valley, and currently lives in Paris, France. He has a degree in Econometrics and a patent in mobile analytics. 

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Blockchain: Much Ado About Nothing? How Very Wrong!

Juergen Roehricht

Let me start with a quote from McKinsey, that in my view hits the nail right on the head:

“No matter what the context, there’s a strong possibility that blockchain will affect your business. The very big question is when.”

Now, in the industries that I cover in my role as general manager and innovation lead for travel and transportation/cargo, engineering, construction and operations, professional services, and media, I engage with many different digital leaders on a regular basis. We are having visionary conversations about the impact of digital technologies and digital transformation on business models and business processes and the way companies address them. Many topics are at different stages of the hype cycle, but the one that definitely stands out is blockchain as a new enabling technology in the enterprise space.

Just a few weeks ago, a customer said to me: “My board is all about blockchain, but I don’t get what the excitement is about – isn’t this just about Bitcoin and a cryptocurrency?”

I can totally understand his confusion. I’ve been talking to many blockchain experts who know that it will have a big impact on many industries and the related business communities. But even they are uncertain about the where, how, and when, and about the strategy on how to deal with it. The reason is that we often look at it from a technology point of view. This is a common mistake, as the starting point should be the business problem and the business issue or process that you want to solve or create.

In my many interactions with Torsten Zube, vice president and blockchain lead at the SAP Innovation Center Network (ICN) in Potsdam, Germany, he has made it very clear that it’s mandatory to “start by identifying the real business problem and then … figure out how blockchain can add value.” This is the right approach.

What we really need to do is provide guidance for our customers to enable them to bring this into the context of their business in order to understand and define valuable use cases for blockchain. We need to use design thinking or other creative strategies to identify the relevant fields for a particular company. We must work with our customers and review their processes and business models to determine which key blockchain aspects, such as provenance and trust, are crucial elements in their industry. This way, we can identify use cases in which blockchain will benefit their business and make their company more successful.

My highly regarded colleague Ulrich Scholl, who is responsible for externalizing the latest industry innovations, especially blockchain, in our SAP Industries organization, recently said: “These kinds of use cases are often not evident, as blockchain capabilities sometimes provide minor but crucial elements when used in combination with other enabling technologies such as IoT and machine learning.” In one recent and very interesting customer case from the autonomous province of South Tyrol, Italy, blockchain was one of various cloud platform services required to make this scenario happen.

How to identify “blockchainable” processes and business topics (value drivers)

To understand the true value and impact of blockchain, we need to keep in mind that a verified transaction can involve any kind of digital asset such as cryptocurrency, contracts, and records (for instance, assets can be tangible equipment or digital media). While blockchain can be used for many different scenarios, some don’t need blockchain technology because they could be handled by a simple ledger, managed and owned by the company, or have such a large volume of data that a distributed ledger cannot support it. Blockchain would not the right solution for these scenarios.

Here are some common factors that can help identify potential blockchain use cases:

  • Multiparty collaboration: Are many different parties, and not just one, involved in the process or scenario, but one party dominates everything? For example, a company with many parties in the ecosystem that are all connected to it but not in a network or more decentralized structure.
  • Process optimization: Will blockchain massively improve a process that today is performed manually, involves multiple parties, needs to be digitized, and is very cumbersome to manage or be part of?
  • Transparency and auditability: Is it important to offer each party transparency (e.g., on the origin, delivery, geolocation, and hand-overs) and auditable steps? (e.g., How can I be sure that the wine in my bottle really is from Bordeaux?)
  • Risk and fraud minimization: Does it help (or is there a need) to minimize risk and fraud for each party, or at least for most of them in the chain? (e.g., A company might want to know if its goods have suffered any shocks in transit or whether the predefined route was not followed.)

Connecting blockchain with the Internet of Things

This is where blockchain’s value can be increased and automated. Just think about a blockchain that is not just maintained or simply added by a human, but automatically acquires different signals from sensors, such as geolocation, temperature, shock, usage hours, alerts, etc. One that knows when a payment or any kind of money transfer has been made, a delivery has been received or arrived at its destination, or a digital asset has been downloaded from the Internet. The relevant automated actions or signals are then recorded in the distributed ledger/blockchain.

Of course, given the massive amount of data that is created by those sensors, automated signals, and data streams, it is imperative that only the very few pieces of data coming from a signal that are relevant for a specific business process or transaction be stored in a blockchain. By recording non-relevant data in a blockchain, we would soon hit data size and performance issues.

Ideas to ignite thinking in specific industries

  • The digital, “blockchained” physical asset (asset lifecycle management): No matter whether you build, use, or maintain an asset, such as a machine, a piece of equipment, a turbine, or a whole aircraft, a blockchain transaction (genesis block) can be created when the asset is created. The blockchain will contain all the contracts and information for the asset as a whole and its parts. In this scenario, an entry is made in the blockchain every time an asset is: sold; maintained by the producer or owner’s maintenance team; audited by a third-party auditor; has malfunctioning parts; sends or receives information from sensors; meets specific thresholds; has spare parts built in; requires a change to the purpose or the capability of the assets due to age or usage duration; receives (or doesn’t receive) payments; etc.
  • The delivery chain, bill of lading: In today’s world, shipping freight from A to B involves lots of manual steps. For example, a carrier receives a booking from a shipper or forwarder, confirms it, and, before the document cut-off time, receives the shipping instructions describing the content and how the master bill of lading should be created. The carrier creates the original bill of lading and hands it over to the ordering party (the current owner of the cargo). Today, that original paper-based bill of lading is required for the freight (the container) to be picked up at the destination (the port of discharge). Imagine if we could do this as a blockchain transaction and by forwarding a PDF by email. There would be one transaction at the beginning, when the shipping carrier creates the bill of lading. Then there would be look-ups, e.g., by the import and release processing clerk of the shipper at the port of discharge and the new owner of the cargo at the destination. Then another transaction could document that the container had been handed over.

The future

I personally believe in the massive transformative power of blockchain, even though we are just at the very beginning. This transformation will be achieved by looking at larger networks with many participants that all have a nearly equal part in a process. Today, many blockchain ideas still have a more centralistic approach, in which one company has a more prominent role than the (many) others and often is “managing” this blockchain/distributed ledger-supported process/approach.

But think about the delivery scenario today, where goods are shipped from one door or company to another door or company, across many parties in the delivery chain: from the shipper/producer via the third-party logistics service provider and/or freight forwarder; to the companies doing the actual transport, like vessels, trucks, aircraft, trains, cars, ferries, and so on; to the final destination/receiver. And all of this happens across many countries, many borders, many handovers, customs, etc., and involves a lot of paperwork, across all constituents.

“Blockchaining” this will be truly transformational. But it will need all constituents in the process or network to participate, even if they have different interests, and to agree on basic principles and an approach.

As Torsten Zube put it, I am not a “blockchain extremist” nor a denier that believes this is just a hype, but a realist open to embracing a new technology in order to change our processes for our collective benefit.

Turn insight into action, make better decisions, and transform your business. Learn how.

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Juergen Roehricht

About Juergen Roehricht

Juergen Roehricht is General Manager of Services Industries and Innovation Lead of the Middle and Eastern Europe region for SAP. The industries he covers include travel and transportation; professional services; media; and engineering, construction and operations. Besides managing the business in those segments, Juergen is focused on supporting innovation and digital transformation strategies of SAP customers. With more than 20 years of experience in IT, he stays up to date on the leading edge of innovation, pioneering and bringing new technologies to market and providing thought leadership. He has published several articles and books, including Collaborative Business and The Multi-Channel Company.