PowerPoint Presentation

[Audio] Welcome to the Coca-Cola way for repeatable Experimentation at Scale Playbook video learning modules. First up, Module 1, What is Experimentation at scale?.

[Audio] On our journey to becoming the Best Marketing company, we are transforming our ways of working through key initiatives, Experimentation at Scale is one of them, a capability that will be our Superpower bringing us closer to our Vision! E&S came to life as we recognized the need to hack current and future complexity when engaging with consumers, allowing us to accelerate and simplify consumer centered decision making that unlocks marketing Effectiveness and Efficiency which is our Mission! Today we kicked off E&S across 2 verticals: Media and Sustainability. This is just the beginning and we will expand into more verticals in the future..

[Audio] The objective of this playbook is to offer you practical guidance on Experimentation at Scale, by sharing a unified framework, outlining where and how we Experiment at Scale!.

[Audio] As you know our organization has a very interesting learning tool set. Experimentation at Scale is great for expediting consumer centered decision making. Lets begin by clarifying how E@S can complement other learning methods such as Pilots or Research. Starting with research, this learning tool is focused on open, longer-term investigation across deep questions to solve business challenges with maximum accuracy. Experimentation on the other hand, is a hypothesis driven, agile test approach to get learnings faster. When we add the "scale" element to Experimentation, the tool learning elevates. We follow a hypothesis driven agile approach that is linked to a globally aligned scalable learning agenda. Through proving or disproving hypotheses through agile experimentation, insights and best practices can be decoded for re-application in our marketing practices laddering up to driving sales and weekly +. The other learning tool is Pilot which is a Small-scale, time-bound initiative to prove a concept in market and decide improvements before full launch. Lastly are tracking and ongoing optimization learning tools which aim on delivering continuous measurement and identification of opportunity areas to drive improvement..

[Audio] A typical experiment process starts by ideating and prioritizing on the experiments – this can be done via developing a hypotheses that aligns to a learning need while also Leveraging prior experiments & learnings . We expect experiment prioritization to be based on expected value. The next step is around Experiment design, whereby we select the right methodology for the experiment and define our KPIs for measurement and our success criteria. After that we proceed to set up and execution while monitoring the results and taking necessary actions as needed. Next is the measurement and analysis stage where we spend time to analyze results and determine conclusivity of the experiment. And from that we finally capture insights and apply the learnings..

[Audio] When it comes to Experimentation at Scale, there a few differences that get introduced to the typical experimentation process Which enable generating global insights for scaling and embedding into Marketing practices. The first difference is the beginning which includes the learning agenda. Based on business priorities, we have a co-created set Global Learning Agenda that covers the Key questions to answer through experimentation. So when we ideate and prioritize experiments we ensure they are aligned to the global learning agenda. And when it comes to the experiment design we have a few methodologies offered within our portfolio to choose from, which we will dive deeper into in later sections of the learning modules. And finally the last difference would be related to scaling the learnings in a way that informs brand strategy, persistent platforms, E2E Experiences, innovation pipeline and resource allocation.

[Audio] So now that you have a clearer idea on the learning tools we have, and how experimentation vs experimentation at scale operate, we are offering you here a decision tree that can assist you as you decide on whether an experiment or experimentation at scale would be more suitable for your needs..

[Audio] Would you like to take a quick quiz, think about the difference between a typical experiment and experimentation at scale. The correct answer will appear on in a couple of seconds.

[Audio] That's right, the difference between a typical experiment and experimentation at scale is that experimentation at scale is geared towards achieving globally scalable learnings..