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Benchmarking the Business Case for SAP S/4HANA

SAP S/4HANA offers enterprises tremendous potential to go beyond performance and simplicity and deliver significant business value as part of an enterprise-wide digital transformation, but this approach must be understood, considered and incorporated into

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Financial Management Impact of Robotic Process Automation and Artificial Intelligence

Keeping pace with technology in financial management can be a tricky endeavor. Intelligent automation (IA) has caught the attention of finance professionals at enterprises large and small and is being adopted at impressive rates. But what exactly is IA? It is the breadth and complexities of mechanizations, such as robotic process automation (RPA) and artificial intelligence (AI), existing on a technology-spectrum defined as IA. While innovation buzzwords such as machine learning (ML) and trends like RPA abound, it’s helpful to slow down the bandwagon before jumping on it to understand exactly what these buzzwords and trends mean. In terms of financial technology considerations, it’s crucial to understand such differences. So, this is exactly what this blog is devoted to — where we will look at what RPA, ML, and AI truly mean.

Robotic process automation (RPA) essentially is advanced automation that mimics the process and steps taken by its human counterpart. It initially requires programming and guidance to accomplish steps, but once the programming is complete, the robotic component of the process can take over, thereby removing the need for manual processing or intervention.

RPA is adept for rudimentary and often highly repetitive process. It can execute more basic tasks without human intervention and is also referred to as “unattended RPA.” On the lower rung of the IA spectrum is “attended RPA” (or “desktop RPA”), which requires human assistance and works in tandem. The differences between the two are the following:

  • Attended RPA: Bots respond to employee-triggered actions by automatically completing certain tasks to simplify a workflow.
  • Unattended RPA: Bots automatically complete back-office functions at scale with minimal employee intervention.[i]

Within finance, AR processing is an example of an operation that can benefit from RPA. For example, the data found in AR billing systems reflecting successful delivery of a product can then trigger an automated remittal of an invoice to the customer. There is no need for human intervention once the tasks and executable parameters are established. The repetitive process of sending invoices may be transitioned over to the RPA solution.

Machine learning (ML) has a much higher degree of algorithmic, computer-driven automation. Where RPA operates strictly within the parameters of its programming, ML has more freedom and ability to operate because its functions are greatly predicated on adaptive capabilities. These capabilities derive from its ability to learn and predict outcomes; hence the name “machine learning.” Learning via algorithm, in simple terms, translates to considering all inputs and variables and potential outcomes, as well as identifying (and avoiding) potentially problematic areas. Based on the anticipated best outcome, it then works to make this best outcome a reality. The greater the number of inputs and data, the more accurate or perceptive the outcome.  

ML is being explored by internal audit and financial control teams. Those employees executing reviews often must interact with varying systems and teams to retrieve random samples/evidence of adherence to financial controls to satisfy auditing. This can be an intensely time-consuming and rather mundane process. However, when the audit review steps and procedure are programmed as inputs and variables to the ML algorithms, the outcome is the financial review and control process may now be automated. According to an article in CPA Journal: “Rather than relying primarily on representative sampling techniques, ML algorithms can provide firms with opportunities to review an entire population for anomalies.”[ii] As long as the initial inputs and algorithms, as well as the anticipated final outcomes, of course, are approved by the audit team, this task may effectively be taken out of human hands.  

Artificial intelligence (AI) mimics human intelligence, while RPA mimics human actions — to put it clearly; AI is the culmination of robotic learning. ML is not unlike a precursor to AI in that it established the foundations and training on which AI operates. AI does not require additional information nor data from its existing, pre-trained foundation to learn. Rather it aggregates and analyzes historical data to make predictive and learned responses from previous operations devoid of human input or interjection. For ML to make a more advanced predictive response, it would still require additional inputs into its programming algorithm. AI makes its own inferences based on its machine-learned experiences. More so, AI can operate on a broader spectrum by incorporating tools such as generative adversarial networks to stress test and improve neural networks by having them learn from and test each other.

AI working in tandem with deep data creates a very attractive proposition. For example, AI can aggregate customer data and historical trends as well as use predictive analysis to anticipate future purchase and payment behavior. This capability supports multiple business functions and some of their tasks such as risk management in finance or upselling in marketing and sales. It’s no wonder that AI is given so much consideration at all business levels.


The figure below shows the transition just described — from attended RPA, which requires manual intervention, through RPA and ML, to complete data-driven AI with deductive analysis.

 Machine Learning blog image

                                                                                                                                                                 Source: Medium.com

Figure caption: As the automation increases in complexity – going from process-driven action to data-driven cognition – so too do the costs rise.

What Does This Mean for SAPinsiders?

  • Embrace financial technology integration. The growing interconnectivity between process capabilities and data integration is almost boundless. Those organizations that recognize the benefits of adopting systems that can integrate enterprise-wide processes and particularly finance functions (such as SAP S/4HANA) and analysis (such as SAP Analytics Cloud) will ultimately prove to be more efficient and insightful. IA paves the way to this road. 
  • Maximize value-added tasks with your employees by automating mundane tasks. Process map and identify where RPA, ML, and AI can potentially execute tasks previously manually managed.  Conversely, identify areas where increased employee attention will be well served, such as retention-based efforts, and transition resources accordingly.
  • Identify relevant existing and anticipated benefits of IA in finance. As was briefly described, the benefits range from more process-oriented tasks, such as invoice management and payment remittal, to more complex functions, such as general-ledger management, to critically valuable tasks, such as risk management and predictive purchase behavior. The degree to which IA can assist largely depends on an organization’s willingness to invest in the technology and its level of commitment.
  • Organizations should develop consistent technology reviews. It’s very likely that within six to twelve months’ time, this blog will be antiquated and obsolete, potentially missing the next advent of technology. That is simply due to the rapid pace at which technology advances. Don’t let this happen to your organization! To avoid having financial technologies experiencing similar obsoletion, schedule periodic reviews that formally address the operational, strategic, and technological goals with comprehensive assessments.

[i] Vartul Mittal, Medium.com “RDA vs. RPA: Attended vs. Unattended Automation”, May 2018 https://medium.com/@vratulmittal/rda-v-s-rpa-i-e-attended-vs-unattended-automation-33a5c729f8a3

[ii] Gabe Dickey, Sandra Blanke, and Lloyd Seaton, CPA Journal “Machine Learning in Auditing” June 2019 www.cpajournal.com/2019/06/19/machine-learning-in-auditing/




Why Customers Need to Build a Measurable Business Case for Employee Central

A successful transition to a cloud-based core HR solution like SAP SuccessFactors Employee Central requires more than just a project plan. For an Employee Central project to succeed, you must undertake a critical review of existing business processes, closely align with HR’s strategic goals, and – most importantly – obtain buy-in from the highest levels of your organization. Securing that buy-in requires a solid business case that is based on measurable results.

Why Build a Business Case for Moving Core HR to Employee Central?

The idea of building a business case to support a significant investment in a core HR solution like Employee Central is not a new concept. Yet in a recent HR-focused SAPinsider survey (of 278 individuals across 129 SAP customers), 31% of all respondents indicated that the lack of a business case is preventing their organization from moving all or some of its legacy HR applications to the cloud.

Among respondents who indicated they are generating HR business results equal to their peers (we will call them “the industry average”), 42% cited the lack of a business case as the number one impediment to adopting cloud HR solutions like Employee Central. The primary reasons given by industry average respondents for their inability to build a business case center around measurements. These reasons include the absence of meaningful key performance indicators (KPIs) and an overall lack of understanding about the capabilities of the cloud HR applications.

Leaders Rely More Heavily on Measurements to Track Success

As we dug deeper into how different respondents measure success, we found more key differences between survey participant groups. Those respondents who indicated they are achieving HR cloud technology results that are slightly better or significantly better than their peers (we will call them “leaders”) are far more focused on measurements than other participants. Leaders are more likely to invest in cloud HR applications like Employee Central that help them to proactively measure key metrics like employee engagement in support of their HR strategic goals. In contrast, their non-leader peer groups are more likely to be driven by reactive forces such as mandatory cost cutting.

Leaders also tend to use and measure a wider variety of KPIs than the rest of those surveyed. The measurements employed by the leaders enhance their ability to defend the return on investment (ROI) for their cloud HR projects. They include:

  • Time to hire. This is one of the most powerful KPIs leaders use to track both candidate experience and process efficiency with SAP SuccessFactors Recruiting and Employee Central. It provides insight into cost, effort, and quality of hiring processes and is a key part of tracking candidate experience.
  • Employee satisfaction. While there are many ways to measure employee satisfaction, there is no question that solutions and platforms like Employee Central play an integral role in meeting employee experience expectations by offering the intuitive user interface, integrated processes, and the easy access to employment information employees expect.
  • Retention rates. Along with developing and engaging talent, SAP SuccessFactors Talent Management solutions allow employers to assess, understand and strategize employee development in order to maximize retention and reduce turnover costs.

 

What Does This Mean for SAPinsiders?

 

Before building a business case, be sure you fully understand the capabilities of the HR applications you plan to implement. For example, if your KPIs require you to track time-to-hire and cost-to-hire metrics, will your recruitment application provide you with the necessary data points to track them? This answer will help you define the proper measurements that will demonstrate the added value of your planned HR business processes. A solid business case for cloud HR that is based on measurable results can help you:

  • Improve your project’s priority over others — financially. Competition for new project funding is fiercer than ever. Building a business case on a solid foundation of measurable results can help position your project above others in your organization.
  • Elevate HR’s business impact. The leaders in our survey differentiated themselves by their willingness and ability to track hidden employment costs. Demonstrating results like these that affect the bottom line will show the importance of HR to the organization’s overall success and change the perception of HR from a tactical to a strategic function.
  • Reduce risk on HR investments. A business case that uses measurable targets will help keep your efforts focused and lower the risk of a project failing or straying off course.
  • Properly track ROI year over year. A wise project manager once told me, “You can’t prove success if you don’t measure correctly.” As our research found, leaders are more likely to invest in applications that measure key metrics that support their HR strategic goals. Your project’s sponsors will demand long-term accountability, and your planning and the right data and measurements will help demonstrate that.

Following this guidance should help SAP customers properly plan for and measure the results of their cloud HR initiatives. For additional insights and lessons learned, look for the upcoming SAPinsider benchmark report on “State of the Market: How the Cloud is Transforming HR”.




Key Considerations When Planning Your SAP S/4HANA Migration

With so many SAP customers entering the planning phase for their SAP S/4HANA migrations due to the upcoming 2025 deadline to make the move, questions abound on precisely steps companies need to take and in what order. Customers left and right are in dire

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Aligning People, Process And Technology

A customer experience action plan for SAP S/4HANA users

This action-plan was created for SAP S/4HANA users to optimize the key components that make up the customer experience — People, Process and Technology (PPT) — and develop a strategy to align them. Download this e-Paper today!

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A Comprehensive Subledger Solution For Finance Transformation

Simplify accounting for financial products with SAP.

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Digitally Transforming the Supply Chain

Learn How to Successfully Manage Complex Supply Chains as Technology Moves Forward

As supply chains become more complex, and technology continues to evolve at increasingly rapid rate, companies need to embrace innovation to stay competitive and achieve their business goals. So how can SAP customers make sure they are well positioned for this reality — now and in the future? Based on SAPinsider research, this article provides insights into how leaders are leveraging new technologies to transform their supply chains and lay a foundation for success.

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Bringing Automation and Collaboration into the Supply Chain: Overall Trends and the Path Forward

In recent months, SAPinsider has conducted a significant amount of research around solutions for digital supply chain management (SCM) — particularly in the areas of automation and collaboration, both of which our research has revealed as playing a significant role in the successful modernization and optimization of supply chains. To build on that research, and to gain deeper insight into how SAP partners are supporting customers in these areas to help with this transition, we also recently interviewed leadership at itelligence, a company that has extensive experience in these areas.

Here, I share some key insights gleaned from the survey of SAP customers we conducted in the areas of automation and collaboration in the supply chain, as well as what we learned from our conversations with intelligence leadership, including how they view the market and the ways in which they support customers on the journey to a digital supply chain.

Automation and Collaboration Are Key to Digital Supply Chains

In the upcoming SAPinsider benchmark report “Supply Chain Transformation Strategies: IT vs. Operations in SAP Customer Landscapes,” we dive deep into what leaders — respondents to our survey that have accelerated growth due to digital transformation in the supply chain — do differently from others when it comes to responding to market pressures. We found that all survey respondents recognize the importance of meeting customer demands for faster delivery, better quality, and cheaper prices, but the laggards — the bottom 30% of respondents, which are companies that have not yet begun a digital transformation of the supply chain — fail to recognize the importance of collaborating with suppliers. Leaders, on the other hand, prioritize this collaboration. Additionally, laggards have yet to adopt the SAP Integrated Business Planning (IBP) solution or any sort of cloud-based internal collaboration tools for supply and operations planning (S&OP), while leaders have implemented IBP.

In addition to prioritizing collaboration, leaders have started to meet the challenge of more complicated supply chains with multiple channels and more advanced strategic sourcing practices, including the use of advanced automation technologies, such as artificial intelligence (AI) and machine learning. Leaders also pay more attention to the security of their data and their processing abilities because they have implemented Internet of Things (IoT) devices and applications, which multiply the volume of data collected. They integrate this data into harmonized master data solutions, leverage it in planning and forecasting, and use it to automatically update inventory planning.

6 Ways to Pave the Way to a Digital Supply Chain

Taking advantage of automation and collaboration means moving to a digital model — so what does this mean for those that are managing or operating a supply chain? When asked about where SAP customers need to concentrate their efforts to pave the way to a successful digital supply chain, the senior director of cloud solutions at itelligence listed six key areas of focus:

  1. Collaboration with suppliers: Supply chain managers and their suppliers need to collaborate and provide a certain amount of visibility to optimize operations. They need to exchange electronic information quickly in a mobile framework. Right now, most SAP customers do this through email and with some electronic data interchange (EDI). Solutions such as itelligence’s it.x-EDIconnect (which supports the secure exchange of SAP ERP system data with suppliers) and it.vendor (which provides a database overview of suppliers that do not use EDI) help ensure visibility and transparency between partners and suppliers.
  2. Self-service order tracking: Amazon, FedEx, and UPS have made us all grow accustomed to tracking everything we order, and end customers of supply chain organizations expect the same capability.
  3. Accounts payable (AP) automation: While AP might fit more into the finance department, it still must work hand in glove with supply chain operations. Procured goods need to integrate with finance to know when to file electronically and make payments.
  4. SCM master data management: To execute SCM processes at the right time, SAP customers need to accumulate generic data, manage and govern it appropriately, and use it in the right applications to plan, make, deliver, service, and retire products.
  5. Rebate and promotion management: Rebates and promotions — used in the right way — can play a significant role in drawing customers and improving customer retention.
  6. Warehouse management: More accurate inventory means more efficient operations and better customer service. Optimized implementations of solutions such as SAP Extended Warehouse Management (SAP EWM) are key to effective warehouse management.

What Does This Mean for SAPinsiders?

Based on the findings from our research on automation and collaboration in the supply chain, and our conversations with itelligence leadership, the following will help SAP customers plan for a successful transition to a digital supply chain:

  • Whether or not you use SCM applications such as itelligence solutions, address the key areas identified above. Any organization managing or operating a supply chain can surely improve the bottom line and possibly accelerate growth with improved collaboration tools, automated AP, better data management, improved customer retention, lower inventory, and shorter lead times.
  • You have the data, make the most of it. You have all the information and tools you really need in your SAP ERP system. If you cannot figure out how to maximize the value of that data, bring in a partner or consultant to help you modernize.
  • Identify the problems that need solving and the technologies that can help your organization solve them. Sustainability and performance analytics, AI, IoT, demand-driven planning, and mobile applications will draw the most investment over the next two years, but take the time to hold meetings between IT and operations to identify the operational problems that need solving and where you can accelerate growth with better technology.
  • SCM operations managers and IT professionals should align on their organizations’ current capabilities. IT professionals and SCM operations managers need to communicate and align better on the reality of their situations. Operations managers tend to have a more optimistic outlook. While they may have a deeper understanding of the operations capabilities, they likely do not have the strengths they claim in security and harmonized data.

Following this strategic guidance should help SAP customers plan for a digital transformation of the supply chain in a way that leverages what they already have in their SAP ERP system and generates measurable business value. For additional insights and lessons learned, look for the upcoming SAPinsider benchmark report “Supply Chain Transformation Strategies: IT vs. Operations in SAP Customer Landscapes.”

Pierce Owen can be reached at Pierce.Owen@wispubs.com.

itelligence, NTT DATA Business Solutions – is a leading global SAP full-service provider. www.itelligencegroup.com




Simplified Retroactive Rebate Processing with SAP S/4HANA Enterprise Management

Ensure High Performance and Accurate Calculations with the Condition Contract Management and Settlement Functionality

Managing retroactive rebates can be a time consuming and challenging task. This article introduces the condition contract management and settlement functionality available with SAP S/4HANA Enterprise Management, which simplifies this task and ensures high performance and accurate calculations. It walks through the key steps involved in configuring end-to-end retroactive rebate processing with the condition contract management and settlement functionality and highlights the key differences compared to the traditional SAP ERP Central Component (SAP ECC) rebate process.

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