Gamifying Sustainability

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Meet the Experts

Key Takeaways

⇨ Simulating ERP environments can help businesses learn make better decisions in the future.

⇨ Adding in sustainability metrics gives organizations an idea as to how ESG considerations can affect them.

⇨ Bringing carbon analytics into ERP processes may require new organizational roles and behaviors.

In late 2021, SAP released the first version of its Product Footprint Management (PFM) solution. It is a set of cloud-based analytics that enables tracking of carbon emissions across the enterprise. These analytics utilize ERP data and are part of a growing SAP portfolio of ESG (Environmental, Social, and Governance) solutions.

Baton Simulations makes competitive, gamified business simulations that run on live SAP. In teams, participants manage a company, competing against other teams in the same marketplace, all using live SAP S/4HANA. Use cases include enterprise software discovery, requirements elicitation, and end user adoption/enablement.

We originally developed ERPsim for use in university programs at the HEC Montreal business school. Now, over 350 universities that are members of the SAP University Alliance use ERPsim in MBA and undergraduate programs. Baton supports the commercial use by SAP and its ecosystem globally.

The launch of PFM was received with excitement by the R&D teams at Baton and the HEC ERPsim Lab. Both teams believed that adding carbon emissions KPIs to our traditional ERP KPIs (net income, sales, warehousing costs, supplier costs, etc.) could act as a great introduction to sustainability concepts.

Simulation Scenarios

In late Q4 2021, with support from SAP, we released three simulation scenarios incorporating PFM analytics in some of our core ERP simulations: one for energy drinks (with a focus on retail sales), one for dairy products, and one for medical supplies—the latter two focusing on wholesale distribution and logistics. A year later, after 95 sessions with nearly 3,000 participants in EMEA, APJ, and the Americas, we are ready to share some observations.

While these cannot be construed as implementation lessons learned, they do represent the feedback of SAP decision-makers in organizations keen on finding out more about sustainability in ERP. All feedback comes from being hands-on with the real solution for three hours, using Carbon Footprint KPIs connected to a live S/4HANA ERP system. This is definitely more than a PowerPoint demo.

At a time where international standards for financial disclosure are emerging around Scope 1, Scope 2, and Scope 3 greenhouse gas (GHG) emissions, there is obviously interest around the topic, especially from the office of the CFO.

  1. Carbon emissions KPIs can touch nearly everything in ERP

The first observation from many participants is how pervasive carbon emission metrics can be across end-to-end enterprise processes. The SAP PFM team did a remarkable job creating different analytical views around carbon emissions. These include suppliers, warehousing, carbon tax, transportation, raw materials, energy consumption, etc. There is a wealth of information available, but making it actionable proved to be a challenge, at least in the initial stages.

  1. Bringing carbon analytics into ERP processes may require new organizational roles and behaviors

The amount of information may be overwhelming, so many teams choose to dedicate a specific role to these analytics. The carbon analytics person acts as a business partner to the other roles, especially to sales, procurement, and logistics, providing both internal data as well as external competitive information. There were often discussions at the end about where that role would sit in the organization, separate as part of the office of the CFO, or within local operations.

Our simulations are competitive in nature, with winning teams typically sharing the following attributes:

First, they defined clear roles within their team; second, winners communicated constantly, with silent teams never winning. The most frequent feedback we received was how acting on sustainability metrics required an even greater focus on cross-functional collaboration than standard ERP. Teams quickly realized that this was about way more than technology deployment.

  1. How do we define success: The need for corporate governance for carbon metrics

One obstacle to carbon emissions reporting implementation is the lack (or multiplicity) of standards. This is changing. At its October 2022 meeting, the International Sustainability Standards Board (ISSB) of the IFRS Foundation voted unanimously to require company disclosures on Scope 1, Scope 2, and Scope 3 greenhouse gas (GHG) emissions, applying the current version of the GHG Protocol Corporate Standard. While this standard focuses on providing information to potential investors, it will likely shape requirements for carbon emissions analytics for years to come.

That being said, our simulations, at least those designed for the private sector, have always had Net Income as the overarching winning KPI. The leaderboard in our sims is the ranked SAP P&L of each team, something that everyone relates to. Adding carbon emissions forced us to rethink our leaderboard, so we added net income per ton of carbon as an additional winning metric. This highlighted the teams that generated the highest profit with the lowest emissions.

We also added the capability to drill down into the functional areas (supplier selection, replenishment cycles, logistics) where the teams’ operational decisions moved the needle on carbon emissions. In the teams’ debriefing after the sim, there were rich discussions about how corporate dashboards (and individual incentives) may need to evolve. We do not pretend that profit per ton of carbon is the universal answer. Organizations will need to adapt their historical operational KPIs to account for these new variables.

  1. The potential for machine learning applications for sustainability decision-support

In our simulations, we accelerate time in SAP where one day of business transactions takes place in one or two minutes. This artifice creates a sense of urgency and forces participants to make rapid decisions, observe the outcomes, and adapt. This is a well-known accelerated improvement and learning model, used in flight simulators or process improvement programs.

Adding a carbon variable to a multi-variable decision process. Involving pricing, marketing, MRP, and logistics proved quite challenging for some users, especially in the early stages, and even more so for those with limited business operations experience. We suspect that real-life implementation might prove similarly challenging.

However, machine learning algorithms were designed to solve multi-variable equations in real time based on historical data. Being early adopters of the SAP Business Technology Platform, mostly to illustrate how ML can boost ERP performance, we made it possible for the participants in the later part of the experience (it’s good to struggle a bit first) to activate decision-support bots. The ML bots used the data generated in the simulated marketplace to train. That way, they could suggest an optimal decision, learn what is happening in the ERP system, and ingest market data on the other teams.

An example might be to lengthen replenishment cycles (fewer deliveries), but possibly augmenting warehousing expenditures, each with their own associated carbon footprint. Finding the right balance, while maximizing margins, is a worthy ML application. Another might be to procure a local, higher-priced, sustainable product but predict demand from consumers willing to pay more for a product advertised with lower carbon emissions.

  1. Crawl, walk, run toward a sustainability implementation maturity model

Most organizations we have engaged with are still in the early stages of carbon analytics adoption. They need more awareness and education, especially with senior executives. Some organizations are outliers and well on their journey. It is too early to have statistical data on market adoption, but the feedback we received provides interesting anecdotal evidence on how organizations embark on a carbon footprint implementation journey, each step building on the previous one.

Step 1: Measurement

SAP PFM is a solid starting point to provide visibility into carbon emissions if they are captured in the core ERP system. The upcoming IFRS requirements will facilitate this data capture going forward both internally and across supplier networks. The SAP Ariba Industry Supplier Business Network already offers some add-on to track supplier sustainability performance. Given the IFRS mandatory requirements for publicly listed companies, this is a solid first step.

Furthermore, speaking from personal experience with deploying ERP governance best practices, a dashboard is a powerful change management tool. What gets measured gets done. It is important to note that SAP is positioning PFM as one pillar of its Sustainability Control Tower. Other pillars focus on governance and social responsibility indicators.

Step 2: Insight to action, empowering operational business users

Once data is collected for reporting purposes, the next step should be to make it actionable within ERP processes. This requires focus to avoid overwhelming operational users. It also necessitates clear governance guidelines as to where to target emissions reduction. Supplier selection, with the latest versions of S/4HANA now including visibility into carbon footprint directly from standard SAP Fiori apps, might be a good way to start. Transportation and logistics is another area with potential low-lying fruits. Empowerment is key here. Users must be able to see the impact of their actions and realize they are making a difference.

Step 3: Cross-functional, enterprise-wide sustainability strategy

A common objection to sustainability programs is, “Yes, but at what cost?” with sustainability as a source of profit being perceived as PR spin. While our simulations are synthetic environments, the equations driving consumer demand are based on realistic economic models. It is interesting to see participants discover by themselves, using real-time cross-functional enterprise data, that a product with a higher cost, sourced locally, with the right marketing, can actually be quite profitable.

This invariably leads to comments like “Why don’t we have this visibility?” from users. We saw similar conversations around transportation and logistics. This often included the added context of disrupted long-distance supply chains providing reinforcement for locally sourced products.

After a year of experience, one thing is clear: people want to make a difference. Many do in their personal consumer life. Yet having an even greater impact as corporate citizens is a source of enthusiasm. Tapping into this positive energy should drive momentum for sustainability corporate initiatives.

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