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A Business Transformation Perspective

Innovation in today’s digital and data-driven age, is the fuel to keeping organizations afloat amongst evolving technology and fierce competition. Against the expectation to continually deliver ‘bursts’ of innovation and agility for future growth, SAP customers are looking for more than just a standard move to SAP S/4HANA. They are looking for opportunities to work closely with product management, to define and shape upcoming solutions through partnership and co-innovation.

Co-innovation catalyzes a deeper customer engagement, which can provide Product Management unparalleled feedback around solution efficacy and present an early success qualifier for upcoming solutions. A key prerequisite to any co-innovation opportunity is the demonstration of customer value or business outcomes. For customers to invest their time, resources and data, they must assess the benefits that the proposed solution would bring to their business, against the outflow of resources that it would consume.

A vital question which then emerges on this prerequisite, is how should Product Management demonstrate the value of upcoming solutions? The answer is, through creating 1:1 traceability between a customer’s objectives and/or specific pain-points to a quantifiable P&L impact achieved or enabled by the Intelligent Technologies. The roadmap to navigate to this P&L impact is covered in four broad steps which are detailed in the sections below.

Step 1: Frame the Storyline

The essence to any Product strategy involves the ideation for addressing a gap, or resolving obstacles commonly faced across a process, line of business or industry. In context of Intelligent Technologies, this would involve the articulation of the pain-point / objective that the solution has been developed to address. These could include inefficient use of resources, wasted productivity, high margin of errors and business process bottlenecks just to name a few. Clarity on, for example, the pain-point addressed would empower the customer to relate the problem statement to their own organizational processes and pre-emptively visualize the resolution of their challenges with the SAP Intelligent Technologies.

The next action would entail connecting each pain-point to the solution capability. This demonstrates how each of the solution capabilities work to resolve the identified pain-points. With the development of this connection, Product Management would have the ability to justify the use of the Intelligent Technologies in the customer’s landscape, with direct transparency to each of the challenges reduced or resolved.

The implementation of any technology brings consequences which can impact the customer’s landscape to varying degrees. Therefore, the next sequence in the storyline progression is to marry the impact of the solution to the outcomes it will produce across the customer’s people, process and technology elements. For instance, the use of the Intelligent Technologies may leverage automation, which could influence productivity gains (people), a condensed end-to-end cycle time (process) and reduce dependency on other third-party analytical tools (technology). Identifying impacts across these domains enables the customer to envisage how the Intelligent Technologies is able to produce tangible improvements relatable to the organization’s inner workings.

Step 2: Determine Value Drivers

Once the potential change impacts are qualified, they are then converted to value drivers. Value drivers are vehicles to demonstrating improvements and materialize directly from the change impacts. Value drivers can be strategic (non-tangible) or quantifiable (tangible) in nature and differ from each other given their link to a customer’s P&L. The split between strategic vs. quantifiable value drivers depends on the nature of the customer’s business and industry.

Strategic or non-tangible value drivers can include improvement in customer satisfaction, reduction in exposure to risk, betterment in compliance and improvement in employee engagement to name a few. These are considered “soft” benefits which may prove fruitful in an analysis of causality, however, may not carry a 1:1 traceability to individual P&L elements.

Quantifiable or tangible value drivers may include an improvement in process cycle time, a betterment of days in inventory, reduction in cost of sales, and reduction in inventory carrying costs, amongst others. These value drivers are “hard” benefits which have a 1:1 traceability to individual P&L elements. These include SG&A (Sales, General & Administrative Expenses), Working Capital, Pre-Tax Margin, Revenue, or COGS (Cost of Goods Sold). Benefits may be recurring or a one-time improvement (e.g. working capital). Given that the objective of this thought leadership is to demonstrate customer value of Intelligent Technologies from a P&L perspective, our focus will be on benefits that carry direct traceability to a customer’s P&L.

Value drivers can differ by industry, line of business, or process. They each have unique parameters which require quantification with customer data. SAP provides standard value drivers from the Value Lifecycle Manager (SAP VLM) tool. These value drivers have been authored with a pre-built link to the various P&L elements. They require careful selection based on a combination of the change impact, the line of business and the specific process the Intelligent Technology is addressing.

If standard value drivers do not match the benefits enabled by the Intelligent Technology, alternate value drivers can be created with custom parameters to match the customer circumstance. In this instance, one must use the change impact of the technology solution as a basis to understand where the solution improves people, process and technology elements, and customize parameters accordingly.

Step 3: Baseline, Benefit Target & Timing

Once value drivers have been selected with defined parameters, establishing a baseline is required. Baselining is the practice of taking an “as-is” measurement and determining the base that is associated with performing that activity or process without the implementation of new technology. Baselining enables the customer to understand the starting cost-base attributed to their current processes and solution use.  A baseline furthermore serves as an agreed reference point against which future performance may be compared.  In addition, it is also the reference point for metrics and calculation methods for future measurements.

Collecting the baseline consists of gathering customer data for each parameter of the value drivers selected. It is noteworthy to mention that customer data points for each parameter may be available via system reporting or may require measurement using other practically relevant methods. Understanding the customer’s organizational structure and processes is key to collecting the baseline. While a small to medium-sized customer which has organically grown may have singular divisions and processes being performed centrally, a large customer or conglomerate, grown inorganically (e.g. via M&A) could have multiple divisions across geographies, including several instances of decentralized processes and business functions. Having this understanding will aid in collecting data and bring opportunities to further apply the Intelligent Technology to additional areas.

Once baselining has been completed, Product Management should have an agreed starting point to sharing benchmarks or expected improvement ranges for each of the value drivers. Benchmarks may be obtained via previous studies or results from PoCs (proofs of concept) or through using standard benchmarks collated in the SAP Value Lifecycle Manager. In the absence of these sources of data, a target setting approach should be utilized. This approach involves setting mutually agreed targets for achievement based on the accuracy of the Intelligent Technology (e.g. 91% accuracy in making predictions or providing recommendations, etc.).

With the understanding that new solutions may not always have previous benchmark data, or volume of PoC-runs to suggest improvement ranges, benefit targets should be evidence-based. In the absence of this evidence, Product Management would need to, at least, initially rely on the potential change impacts identified. These change impacts would help to estimate the magnitude of benefits across each component (people, process, and technology). Additionally, Product Management may also combine this information with the technical features and capabilities of the Intelligent Technology to methodically propose benefit ranges. These improvement ranges would then serve as targets, rather than realistic achievable potential. This improvement range would become the value aspiration in lieu of benchmarking data.

Once improvement ranges have been suggested, next in sequence is to establish timing of benefit achievement. With the implementation of any solution, it is neither logical nor feasible to assume it would always produce benefits on day one. New technology implementation requires a stabilization period in which solution adoption, process maturity and acceptance of change occur. With the implementation of SAP ERP, this stabilization period has historically been estimated at one year. That is, benefits begin to accrue after the one-year mark. With Intelligent Technologies however, experience suggests a stabilization period closer to the three to four-month mark.

Under this guidance, benefit timing would need to be agreed. For each value driver, the proposed improvements would need to be broken down into phases towards full achievement. For example, if a benefit demonstration period for a selected Intelligent Technology is 18 months, then this period could be equally divided into three parts: value achieved between 0 – 6 months; 6 – 12 months; or 12 –18 months. During each of these periods, there would need to be an estimation on percentage of benefits estimated for achievement. For example, 20% achievement of total benefits in period one (0 – 6 months), 50% achievement in period two (6 – 12 months), and 100% achievement in period three (12 – 18 months). Working capital benefits may accrue to a cumulative value of 100% throughout the benefit demonstration period, where recurring benefits may be continuous and repeating throughout this period.

With the use of such a ramp-up strategy benefits realization can be scaled appropriately alongside system stabilization. This reduces the risk of over-promising and serves as a reality-check with known perils associated with digital transformation.

Step 4: Impact to P&L, Costs & Cashflow

The last step in sequence is to identify how each value driver influences different elements of the P&L and the consequent contribution of each of these elements to cash flow. A P&L statement consolidates revenue sources and compares them against the cost of sales and additional expenses incurred. The intent of any P&L statement is to reflect the net income or loss produced during the reporting period under consideration. In the context of demonstrating benefits that the Intelligent Technologies would bring; each value driver requires direct traceability of the benefit to the various elements comprising the P&L.

Value drivers that improve through reducing the cost of goods or services sold would be linked to COGS element of the P&L. For instance, these may include a betterment in procurement of material, production, or labor costs associated with manufacturing.

Value drivers that reduce the expenses associated with selling (indirect and direct) would be linked to the SG&A element of the P&L. These would include all expenses such as HR, Finance, Marketing, Outbound transportation of finished goods, etc.).

Value drivers that reduce expenses not falling under COGS or SG&A, would be linked to Pre-tax margin. This type of expense betterment would apply to both raw materials and finished goods.

Although not impacting the P&L statement, those value drivers that improve the cash position would fall under Working Capital. Working capital benefits are typically one-time benefits that accumulate up to a maximum of 100%. These may include improvement in Days Sales Outstanding (DSO), Days in Inventory, and Days Payable Outstanding (DPO).

Lastly, any value drivers improving revenue, would be linked to the revenue element in the P&L. These may include bettering revenue potential through reducing stock-outs and upsell opportunities amongst others. The table below provides general guidance and details on tracing value drivers to a corresponding P&L element.

PL Impact Areas

To generate a net cashflow against the total value of improvements, costs would need to be consolidated for comparison against the inflows expected. Cost categories may include implementation costs, cost of internal and external resources, subscription costs and hardware costs. These costs are situational and may also vary depending on the Intelligent Technology in question. Cost assumptions and understanding should thoroughly be vetted prior to use across any value-based model. Incorrect cost assumptions may overstate the net cashflow expected and may also set the incorrect commercial expectations with the customer. Therefore, it is vital to ensure all cost assumptions are thoroughly researched, validated and formalized prior to use.

Based on the culmination of all steps, the final output of the customer value case would be the cashflow. The cashflow analysis would represent all inflows of cash expected from betterments against the outflows from cost categories related to the implementation of the Intelligent Technology. Based on the stabilization period and recommended guidance on day one, the expectation would be to have a negative cash outflow at the onset of the implementation. This would be followed by accrual of benefits which would incrementally turn cashflow to positive over a period of time.

Based on the cashflow statement, Product Management would be able to demonstrate key figures such as the Net Present Value (NPV) of the investment, the Return on Investment (ROI), as well as the payback period. The NPV would represent the current value of all expected future cashflows. The use of the NPV would demonstrate to the customer whether the expected financial gains of an Intelligent Technology would outweigh its cost in present day terms. The ROI would be represented by taking the difference between the expected gains and the cost of the investment, divided by the total cost of the investment. The payback period would represent the number of months or years that the customer would require to recuperate their investment. Thus, the combination of these key outputs would demonstrate the Customer Value case for the Intelligent Technology in question.

Risk in Context of Positioning Value

With any value case or model which relies on assumptions and benchmarks, there is an element of risk that the benefit potential may not be realized. This could be associated with over estimation of improvement targets or understating the costs. Benefit realization may also be influenced by external factors that may be out of the boundaries of control and require strong Organizational Change Management or material dependency on customer employee execution to materialize.

These risk factors should be clearly identified, articulated and documented during the customer value case demonstration. Weighing the benefits against the associated risks, the customer would make a judgement call to accept the investment at the current time, defer the investment decision to a later period, or decline the opportunity altogether. The customer value case is the logical mechanism by which all potential gains, costs and risks can be communicated with full transparency to the customer.

The customer value case can also provide internal benefits to Product Management teams, by enabling 1:1 traceability from features and capabilities of Intelligent Technologies, to the benefits they may help customers achieve. In this way, the customer value case could further provide opportunities to make solutions more robust, integrated and focused on delivering business value and outcomes.


The Customer Value Case Framework to Assess Benefit Potential undoubtedly supports SAP’s stated intent to drive customer engagement around SAP solution enabled outcomes.  It is a useful approach and tool for articulating potential benefits resulting from customer investment in SAP technology and innovations. It provides a targeted and systematic means for working jointly with customers to define and agree a framework, defined measures and baseline for making potential benefits visible. Used in conjunction with SAP solution’s measurement capabilities it provides the ability to measure actual performance and benefits achieved on a comparable basis with customer baseline data. Due to its process-centric departure point, that can be extended to P&L level, it supports an outcomes-based engagement at levels beyond the mere project-level, to be operationally and strategically relevant for the customer’s business. These features uniquely position the Customer Value Case Framework as a mechanism for realizing the SAP strategy around outcomes-based engagement and could provide a basis for potential outcomes-based risk/reward models of contracting with customers in future.