The Third Generation Of Budgeting – Agile Planning

Thorsten Jopp

With market trends shifting dramatically and technology reshaping businesses, leading finance organizations recognize that they have to move fast to capitalize on opportunities. And nowhere is this truer than in planning, budgeting, and closing.

For those who work in business intelligence and performance management – as I have for 13 years – this is not a novelty; having the speed and flexibility to change has always been important. But now, with a digital and globally connected economy, the impact of change on finance processes has significantly increased, maybe more than for any other corporate function. Of the different finance end-to-end processes, such as procure-to-pay or order-to-cash, I would like to explore one example: budgeting and planning.

From fixed cycles to dynamic, agile budgeting

Until about 10 years ago, budgeting was usually done in fixed cycles, looking forward a certain number of quarters. Once the end of the planning timeframe was reached, a new cycle started. As business became more dynamic, companies had to adapt their planning process, and a rolling budget was widely established – with the result that live plans could be adopted for the current situation, while an additional period could be planned at the same time.

Today we see the next big change in the way companies set goals – agile planning – which enables companies to plan based on new dimensions. It’s being driven by the fact that companies inside long-standing and stable industries are developing completely new business models.

One example that I found very easy to understand is airplane engines. The original business model for manufacturers was to produce engines and sell them. Today, instead of selling engines, leading organizations are selling “thrust” – which is what the customer ultimately needs.

Such business models become possible because of technological innovations like the Internet of Things (IoT), which, in our example, allows manufacturers to connect their engines to the Internet and gain live usage information that forms the basis for customer invoicing. I look forward to the day when airlines adopting this model provide a partial refund of my ticket price if a flight uses less thrust than they had originally calculated because of a strong tailwind. But maybe this idea will stay a dream…

The impact on financial planning

So what is the impact of these new business models on financial planning? As I said earlier, agile planning means companies can easily adjust the dimensions on which they create their plans. For instance, in our engine example, it would mean not only planning the “volume of engines sold,” but also the “thrust in newtons delivered.”

Technically speaking, this is an additional primary metric and a new dimension in our data model. Adding a new metric is more complex than just adding items to existing dimensions (like a new product). A new dimension has direct and indirect impacts on other parts of the planning process, for example, organizational responsibility (e.g., who controls the planned thrust). Adding a new dimension also affects the transactional enterprise resource planning (ERP) system, which needs to be flexible enough to adopt and deliver the correct actuals for the “plan vs. actual” controlling processes once a new business model is operating.

ERP and budgeting and planning applications have become significantly more flexible in recent years in order to fulfill such requirements. As a result, business planning and consolidation capabilities are now tightly integrated into one environment and include a number of new innovations, such as the “model extension tool.” The result is a very dynamic, flexible planning solution that can accommodate the new business models that are emerging and allow organizations to run agile planning cycles.

Join our Webinar on Sept. 15 at 4 p.m. CEST/10 a.m. EDT to hear PwC discuss the future of finance planning, along with a representative from Kering Eyewear, who will explain how SAP S/4HANA and SAP Planning and Consolidation are helping finance deliver greater value to the business. One of my colleagues from SAP will describe the solution in detail. Register here.

Learn how organizations are gaining instant financial insights and using them to make better decisions – both now and in the future. Register now for the 2017 Financial Excellence Forum, Oct. 10-11 in New York City.

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

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Thorsten Jopp

About Thorsten Jopp

Thorsten Jopp is part of SAP`s global business development team for enterprise performance management, finance and controlling, and analytics. With 13 years experience in budgeting, planning, and business intelligence, he is now focusing on growing innovative ideas and new business processes in the context of digital finance transformation.

The CFO Role In 2020

Estelle Lagorce

African American businessman looking out office window --- Image by © Mark Edward Atkinson/Blend Images/CorbisThe role of the CFO is undergoing a serious transformation, and CFOs can expect their role to continue to evolve, according to a recent CFO.com article by Deloitte COO and CFO Frank Friedman.

In the futurist article, Friedman says one of the biggest factors that will contribute to the CFO’s significant change over the next five years is technology.

Digital technology is obviously expected to drive change in high-tech companies, but Friedman says it’s industries outside of the tech sectors that are of particular interest, as they struggle to understand how to grasp and harness the digital capabilities available to them.

Working with high tech in low-tech industries

Five years from now, a finance team may be defined by how well it uses technology and innovative business tools, regardless of what industry it’s in. The article outlines some examples of ways that digital technology will increasingly be used by CFOs in “non-tech” sectors:

  • Predictive analytics: CFOs in manufacturing companies can forecast results and produce revenue predictions based on customer-experience profiles and current demand, instead of comparing to previous years as most companies still do today.
  • Social media and crowdsourcing: You may not think CFOs spend a lot of time on social media or crowdsourcing sites, but these methods can actually expedite finance processes, such as month-end responsibilities of the finance organization.
  • Big Data: CFOs already have a lot of data at their fingertips, but in 2020 they will have even more. CFOs in both tech and non-tech sectors who understand how to use that data to make valuable, informed decisions, can strategically guide their company and industry in a more digitally oriented world.

To do this, Friedman says CFOs can lead the way by addressing some critical areas:

  1. Know the issues: Gather the key questions that leaders expect Big Data analytics to answer.
  1. Make data easily accessible: Collect data that is manageable and easy to access.
  1. Broaden skills: The finance team needs people with the skills to understand and strategically interpret the data available to them.

The tech-savvy CFO

The role of today’s CFO has already expanded to include strategic corporate growth advice as well as managing the bottom line. In 2020, Friedman says expectations placed on the CFO are presumed to be even greater, and CFOs will likely need a much more diverse, multidisciplinary skill set to meet those demands.

The article details several traits and skills that CFOs will need in order to keep up with the pace of digital change in their role.

  1. Digital knowledge: CFOs must be tech-savvy in order to capitalize on technical innovations that will benefit their company and their industry as a whole.
  1. Data-driven execution: CFOs will need the ability to execute company strategy and operations decisions based on data-driven insights.
  1. Regulatory compliance: Regulations continue to be more stringent globally, so CFOs will need to be proficient at working closely with regulators and compliance systems.
  1. Risk management: With the growing global economy comes increased cyber and geopolitical risks worldwide. The CFOs of 2020, especially those in large multinational organizations, will need to have the expertise to monitor and manage risk in areas that may be unforeseen today.

The future CFO’s well-rounded resume

By 2020, the CFO role will require much more than just an accounting background. According to Deloitte’s Frank Friedman, “CFOs may need to bring a much more multidisciplinary skill set to the job as well as broader career experiences, from working overseas to holding positions in sales and marketing, and even running a business unit.”

So if you’re a current or aspiring CFO, you have five years to round out your resume with the necessary skills to be ready for the digitally driven role of the CFO in 2020.

The above information is based on the CFO.com article What Will the CFO Role Look Like In 2020?” by Deloitte COO & CFO, Frank Friedman – Copyright © 2015 CFO.com.

Want to learn more about best practices for transforming your finance organization? View the SAP/Deloitte Webinar, “Reshaping the Finance Function”.

For an in-depth look at digital technology’s role in business transformation, download the SAP eBook, The Digital Economy: Reinventing the Business World.

To learn more about the business and technology factors driving digital disruption, download the SAP eBook, Digital Disruption: How Digital Technology is Transforming Our World.

To read more CFO insights from a tech industry perspective, read the Wall Street Journal article with SAP CFO Luka Mucic: Driving Insight with In-memory Technology.

Discover 7 Questions CFOs Should Ask Themselves About Cyber Security.

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Estelle Lagorce

About Estelle Lagorce

Estelle Lagorce is the Director, Global Partner Marketing, at SAP. She leads the global planning, successful implementation and business impact of integrated marketing programs with top global Strategic Partner across priority regions and countries (demand generation, thought leadership).

Get Your Payables House In Order

Chris Rauen

First of 8 blogs in the series

Too many organizations ignore the business potential from streamlining accounts payable operations. In a digital economy, however, this may represent one of the best opportunities to improve financial performance and boost the bottom line.

In its recent report, E-Payables 2015: Higher Ground, the research and advisory firm Ardent Partners made a strong case for accounts payable transformation. “In 2015, more AP groups are accelerating their plans to transform their operations and scale to new heights,” states the report.

The digital makeover

From a payables perspective, how you go about fixing outdated procure-to-pay (P2P) practices is much like the decision to improve an aging home. Do you tear your house down and build a new one, or leverage as much of the existing structure as you can and begin a major home improvement project?

There is, of course, a third option. Take no action and make calls to plumbers, electricians, roofers, and other specialists as needed before the house falls apart altogether. While few organizations would consider a “triage” strategy the best option to address deficiencies in P2P operations, many still do. (Just don’t share that with your CFO.)

This blog post is the first in a series that will examine options for upgrading procure-to-pay processes from outclassed to best-in-class. Continuing to focus time and effort on managing transactions just doesn’t make sense. With today’s business networks, organizations have new ways to collaborate with suppliers and other partners to buy, sell, and manage cash.

Automation handles low-value activities, eliminating data entry, exception management, and payment status phone calls. That leaves more time for benchmarking operations, monitoring supplier performance, expanding early payment discounts, and improving management of working capital – the kinds of things that can dramatically improve business performance.

Where do you start?

To begin, you have to recognize that getting your payables house in order is much more than a process efficiency initiative. While cost savings from e-invoicing can be 60% to 80% lower than paper invoicing, there’s much more to the business case.

Improving contract compliance and expanding early payment discounts are other components of a business case for P2P transformation. According to various procure-to-pay research studies and Ariba customer results, the cost savings from getting your payables house in order are conservatively estimated to be $10 million per billion collars of spend. We’ll break down these ROI components in greater detail in future posts on this topic.

The value of alignment

Another important first step, validated by the Ardent Partners report, is getting procurement and finance-accounts payables in alignment. As this is a holistic process, you’ll need to make sure that both organizations are in sync, and you have support from upper management to make it happen.

Now, back to the question: Do you approach a payables makeover to support P2P transformation as a tear-down or a fixer-upper? If your procurement-accounts payable teams are out of alignment, your P2P processes are predominantly paper, and decentralized buying leaves little control over spend, you’re looking at a tear-down to lay the foundation for best practices payables. We’ll share a blueprint with you in the next post in this series.

Chris Rauen is a solution marketer for Ariba, an SAP company. He regularly contributes to topics including e-invoicing and dynamic discounting as well as the value of collaborating in a digital economy. 

Learn more about how to take your payables to the next level of performance in Ardent Partners’ research report “E-Payables 2015: Higher Ground.

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Chris Rauen

About Chris Rauen

In his role at SAP Ariba, Chris Rauen educates procurement, finance, and shared services professionals on the business value of accounts payable automation, procure-to-pay transformation, and collaboration via business networks. Chris has addressed these topics at finance and shared services conferences, in articles for trade and business publications, and in blogs for online communities. Chris has more than 15 years of experience in e-payables, and holds a B.A. in Economics from the University of California, Santa Barbara.

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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Why Artificial Intelligence Is Not Really Artificial – It Is Very Tangible

Sven Denecken

The topic of artificial intelligence (AI) is buzzing through academic conferences, dominating business strategy sessions, and making waves in the public discussion. Every presentation I see includes it, even if it’s only used as a buzzword – its frequency is rivaling the use of “Uber for X” that’s been so popular in recent years.

While AI is a trending topic, it’s not mere buzz. It is already deeply ingrained into the strategy and design of our products – well beyond a mere shout-out in presentations. As we strive to optimize our products to better serve our customers and partners, it is worth taking AI seriously because of its unique role in product innovation.

AI will be inherently disruptive. Now that it has left the realm of academic projects and theoretical discussion – now that it is directly driving speed and hyper-automation in the business world – it is important to start with a review that de-mystifies the serious decisions facing business leaders and clarifies the value for users, customers, and partners. I’ll also share some experiences on how AI is contributing to solutions that run business today.

Let’s first start with the basics: the difference between AI, machine learning, and deep learning.

  • Artificial intelligence (AI) is broadly defined to include any simulation of human intelligence exhibited by machines. This is a growth area that is branching into multiple areas of research, development, and investment. Examples of AI include autonomous robotics, rule-based reasoning, natural language processing (NLP), knowledge representation techniques (knowledge graphs), and more.
  • Machine learning (ML) is a subfield of AI that aims to teach computers how to accomplish tasks using data inputs, but without explicit rule-based programming. In enterprise software, ML is currently the best method to approach the goals of AI.
  • Deep learning (DL) is a subfield of ML describing the application of (typically multilayer) artificial neural networks. Neural networks take inspiration from the human brain, with processors consisting of small neuron-like computing units connected in ways that resemble biological structures. These networks can learn complex, non-linear problems from input data. The layering of the networks allows cascaded learning and abstraction levels. This can accomplish tasks like: starting with line recognition, progressing to identifications of shapes, then objects, then full scene. In recent years, DL has led to breakthroughs in a series of AI tasks including speech, vision, and language processing.

AI applications for cloud ERP solutions

Industry 4.0 describes the trend of automation and data exchange in manufacturing. This comprises cyber-physical systems, the Internet of Things (IoT), cloud computing, and cognitive computing – everything that adds up to create a “smart factory.” There is a parallel in the world beyond manufacturing, where data- and service-based sectors need to capture and analyze more data quickly and act on that information for competitive advantage.

By serving as the digital core of the organization, enterprise resource planning (ERP) solutions play a key role in business transformation for companies adapting to the emerging reality of Industry 4.0. AI solutions powered by ML will be a broad, high-impact class of technologies that serve as a key pillar of more responsive business capabilities – both in manufacturing and all the sectors beyond. As such, ERP must embrace AI to deliver the vision for the future: smarter, more efficient, more flexible, more automated operations.

Enterprise applications powered by AI and ML will drive massive productivity gains via automation. This is not automation in the sense of repetitive, preprogrammed processes, but rather capabilities for software to handle administrative tasks and learn from user behavior to anticipate what every individual in the company might need next.

Cloud-based ERP is ideal for companies looking to accelerate transformation with AI and ML because it delivers innovation faster and more reliably than any onsite deployment. Users can take advantage of rapid iterations and optimize their processes around outcomes rather than upkeep.

Case in point: intelligent ERP applications need to include a digital assistant. This should be context-aware, designed to make business processes more efficient and automated. By providing information or suggestions based on the business context of the user and the situation, the digital assistant will allow every user to spend more time to concentrate on higher-value thinking instead of on repetitive tasks. Combined with built-in collaboration tools, this upgrade will speed reaction to changing conditions and create more time for innovation.

Imagine a system that, like a highly capable assistant, can greet you in the morning with a helpful insight: “Hello Sven, I have assessed your situation and the most recent data – here are the areas you should focus on first.” This approach to contextualized analysis of real-time data is far more effective than a hard-programmed workflow or dump of information that leaves you to sort through outdated information.

Personal assistants have been around in the consumer space for some time now, but it takes an ML-based approach to bring that experience, and all its benefits, to the enterprise. Based on the pace of change in ML, a cloud-based ERP can best deliver the latest innovations to users in a form that has immediate business applications.

An early application of ML in the enterprise will be intelligence derived from past patterns. The system will capture much richer detail of customer- and use-case-specific behavior, without the costs of manually defining hard rule sets. ML can apply predictive detection methods, which are trained to support specific business use cases. And unlike pre-programmed rules, ML updates regularly as strategies – not monthly or weekly – but by the day, hour, and minute.

How ML and AI are making cloud ERP increasingly more intelligent

Digital has disrupted the world and changed the way businesses operate, creating a new level of complexity and speed. To stay competitive, businesses must transform to achieve a new level of agility. At the same time, advances in consumer technology (Siri, Alexa, and Google Now in the personal assistant space, and countless mobile apps beyond that) have created a desire and need for intuitive user interfaces that anticipate the user’s needs. Building powerful tools that are easy to interact with will rely on ML and predictive analytics solutions – all of which are uniquely suited to cloud deployment.

The next wave of innovation in enterprise solutions will integrate IoT, ML, and AI into daily operations. The tools will operate on every type of device and will apply native-device capabilities, especially around natural language processing and natural language interfaces. Augment this interface with machine learning, and you’ll see a system that deeply understands users and supports them with incredible speed.

What are some use cases for this intelligent ERP?

Digital assistants already help users keep better notes and take intelligent screenshots. They also link notes to the apps users were working on when they were created. Intelligent screenshots allow users to navigate to the app where the screenshot was taken and apply the same filter parameters. They recognize business objects within the application context and allow you to add them to your collection of notes and screenshots. Users can chat right from the business application without entering a separate collaboration room. Because the digital assistants are powered by ML, they help you move faster the more you use them.

In the future, intelligent cloud ERP with ML will deliver value in many ways. To name just a few examples (just scratching the surface):

  1. Finance accruals. Finance teams use a highly manual and speculative process to determine bonus accruals. Applying ML to these calculations could instead generate a set of unbiased accrual figures, so finance teams have more time during closing periods for activities that require review and judgment.
  1. Project bidding. Companies rely heavily on personal experience when deciding to bid for commercial projects. ML would give sales and project teams access to decades-worth of projects from around the world at the touch of a button. This capability would help firms decide whether to bid, how much to bid, and how to plan projects for greatest profitability.
  1. Procurement negotiation. Procurement involves a wide range of information and continuous supplier communication. Because costs go directly to the bottom line, anything that improves efficiencies and reduces inventory will make a real difference. ML can mine historical data to predict contract lifecycles and forecast when a purchasing contract is expected so that you can renegotiate to suit actual needs, rather than basing decisions on a hunch.

What does the near future hold?

An intelligent ERP puts the customer at the center of the solution. It delivers flexible automation using AI, ML, IoT, and predictive analytics to drive digital transformation of the business. It delivers a better experience for end users by providing live information in context and learning what the user needs in every scenario. It eliminates decisions made on incomplete or outdated reports.

Digitization continues to disrupt the world and change the way businesses operate, creating a new level of complexity and speed that companies must navigate to stay competitive. Powering business innovation in the digital age will be possible by building and deploying the latest in AI-powered capabilities. We intend to stay deeply engaged with our most innovative partners, our trusted customers, and end users to achieve the promises of the digital age – and we will judge our success by the extent to which everyone who uses our system can drive innovation.

Learn how SAP is helping customers deploy new capabilities based on AI, ML, and IoT to deliver the latest technology seamlessly within their systems

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Sven Denecken

About Sven Denecken

Sven Denecken is Senior Vice President, Product Management and Co-Innovation of SAP S/4HANA, at SAP. His experience working with customers and partners for decades and networking with the SAP field organization and industry analysts allows him to bring client issues and challenges directly into the solution development process, ensuring that next-generation software solutions address customer requirements to focus on business outcome and help customers gain competitive advantage. Connect with Sven on Twitter @SDenecken or e-mail at sven.denecken@sap.com.