How Digitization Can Help Optimize The Account-To-Report Process

Nilly Essaides

There’s a lot that account-to-report (A2R) organizations can do right now to optimize the way they deliver services to stakeholders by standardizing, automating, and centralizing processes and sub-processes and redistributing activities among corporate, global business services (GBS), centers of excellence (COEs), and the business units (BU). Too many activities are still handled at the BU level. Too few are fully automated.

However, digital technologies are bringing finance overall, and A2R specifically, to an inflection point. Digital transformation will not only help make A2R processes faster and more efficient; it will ultimately change the level of the organization at which these processes take place. The introduction of technologies like robotic process automation (RPA) will reduce the need for manual labor and shrink the footprint of the GBS, while promoting greater use COEs, which house high-skill knowledge workers.

According to research conducted by The Hackett Group, the market for RPA is real and growing. It has the potential to change the business process outsourcing (BPO) landscape, GBS organizations, and broader business-specific processes. Adoption is expected to be in the 40%-50% range through 2020, transforming our idea of automation and service delivery. RPA can be a game-changer because it allows companies to achieve substantial cost savings without needing to change their overall technology infrastructure. Process and data must be rationalized and cleaned up, of course, for RPA to work. Everyone dealing with legacy systems knows just how valuable that can be. The same goes for the painful change-management implications that come along with process redesign.

RPA is software that sits between other applications and executes rule-based work that would typically be done by people. RPA mimics human interactions with business applications at the user interface level – for example, logging in and out of an application, copying and pasting data, or choosing from a drop-down menu.

Two big factors are driving RPA adoption in finance and elsewhere:

  1. Speed of impact: RPA has a short development cycle and yields quick benefits like reductions in FTEs, based on low initial investment with a significant ROI in weeks and months, not years.
  1. Enhanced capabilities: RPA-enabled processes are highly auditable and consistent and have extremely low error rates; they are also very scalable and provide the data required to run sophisticated analytics.

When does RPA make sense?

RPA has a wide range of applications within the finance organization because many of its processes fit its application model, specifically those in A2R, such as general ledger entries and reconciliation. Several providers offer end-to-end robotic-enabled solutions that encompass activities such as payables, receivables, tax and treasury, asset management, general ledger and cost, and management accounting. With an RPA-powered close, up to 80% of the process is handled by robots, from accounting system operations, output preparation, period-end closing, internal controls, frequency and quality of transaction processing, and master data maintenance. Only about 20% is manual, including the interpretation of the outcomes and judgment and policy setting.

As A2R executives update the placement and execution of key services considering new digital developments, they should ask the following questions to decide whether a specific process is ripe for RPA:

  • Is the process executed frequently and in large volume? It doesn’t make sense to use a robot to perform a process that happens only infrequently in small batches.
  1. Does the process require access to multiple systems? A robot can much more quickly and efficiently log in/out of applications and cut and paste data from one application to another.
  1. Can the process can be broken down into unambiguous rules? Unlike people, software needs clear rules. If there are judgment calls, it cannot perform its task.
  1. Is the process structured and digital data available? The robots need to follow an established and well-understood set of process steps and have access to all necessary data.
  1. Is the process prone to human error? Robots don’t make mistakes when switching applications and re-inputting data.
  1. Does the process require limited exception-handling? Too many exceptions cause problems for robots. RPA’s ROI is built on doing large volume of repeatable acts. If many of the actions are kicked out for human intervention, it defeats the purpose.
  1. Does the process, once started, require limited human intervention? If the process needs a lot of human intervention, it doesn’t make sense to get robots involved.
  1. How complex is the stakeholder/process ecosystem? Processes that serve multiple stakeholders and exist in very complex ecosystems may not lend themselves well to fully automated solutions because they require different outcomes.

Conclusion

There’s a lot more room for traditional service models to go further and achieve better results. But A2R executives seriously rethinking their service delivery model should evaluate whether it still makes sense to place activities based on the old model, or fundamentally redesign how work gets done using emerging technologies. Ultimately, RPA will alter the traditional finance delivery model and where different activities take place.

For more on digital transformation in finance, see Machine Learning: What’s In It For Finance?

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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).

Artificial Intelligence And Machine Learning Don’t Have To Be Creepy

Tim Clark

Over the past few years I’ve delved into the topic of customer experience, uncovering how new technologies are empowering businesses to know more about their customers than ever before.

While there’s nothing wrong with beer getting smarter at the shelf (and the data that is responsibly collected), it’s obviously not a good idea for businesses to take things too far. No one likes that “close talker” at a cocktail party. They can be downright creepy.

But avoiding the creep factor isn’t easy, especially when powerful capabilities like machine learning and artificial intelligence (AI) are on the guest list—and usually depicted as creepy forces in the world of sci-fi (I’m looking at you Blade Runner and Terminator).

The reality is that AI and machine learning don’t have to be creepy, and they shouldn’t be. It’s what businesses do with their data that matters, and how mutual value and trust are created with customers.

Dealing with doomsday scenarios

So what to make of recent comments from Elon Musk who believes the “global race for A.I. will most likely be the cause of World War III?” Or the notion that Musk has embarked on a “billion dollar crusade to stop the AI apocalypse?” No doubt about it, these are bleak, doomsday predictions of the highest order, coming from a modern-day visionary with access to bleeding-edge info, and they should be taken seriously.

As for machine learning, well, it doesn’t fare much better. Google’s AI chief John Giannandrea recently said he isn’t worried so much about Musk’s warmongering bots, but he is very concerned about “the danger that may be lurking inside the machine-learning algorithms used to make millions of decisions every minute.”

Yikes.

Thankfully, other tech luminaries have a much sunnier disposition about AI and machine learning.

Bill Gates recently told CNBC, “AI will make our lives more productive and creative,” while Mark Zuckerberg believes A.I. is going to make our lives better in the future. As for the doomsday scenarios making headlines, Zuckerberg thinks they are “pretty irresponsible.”

Personalizing the shopping experience

Gates and Zuckerberg’s thoughts are backed by serious research. IDC predicts cognitive/AI capabilities will figure in to some 40 percent of digital transformation initiatives by 2019.

And at SAP’s recent TechEd event, it was revealed that machine learning can help the $2.4 trillion fashion industry with a more personalized consumer experience, according to Margaret Laffan, director of Business Development, Machine Learning at SAP.

“Static window displays of the past won’t work in today’s world of fast fashion and consumer demands for an increasingly more personalized experience,” said Laffan in a recent story, The Ultimate Personal Shopper Is A Machine. “Machine learning gives retailers the speed and intelligence to quickly match the hottest looks with every customer’s fashion style.”

As you can see from this video demo of what this level of personalization looks like, it becomes much easier to understand why AI and machine learning can improve people’s lives without being creepy.

For more on this topic, see Why The Time Is Now For AI And Machine Learning.

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Tim Clark

About Tim Clark

Tim Clark is the Head of Brand Journalism at SAP. He is responsible for evangelizing and implementing writing best practices that generate results across blog channels, integrated marketing plans and native advertising efforts.

Digitalist Flash Briefing: Answers To Two Burning Questions About Conversational AI

Bonnie D. Graham

Today’s briefing looks at a current hot topic – conversational AI and digital assistants for your business – from the perspective of another hot innovation from back in the day.

  • 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.