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      The project in brief

      Achieving sustainable revenue growth is a challenging goal for fast-moving consumer goods (FMCG) businesses. Profit margins can be tight, so pricing has to be right for every market and product brand. For a UK-headquartered European frozen food company, a new revenue growth management (RGM) tool developed by KPMG improves key decision-making and boosts profits.

      From 2021 to 2024, we worked with the company to increase commercial growth opportunities by using better data and management processes that enhance sales and marketing activities. The RGM tool had to be user-friendly, scalable and flexible for different markets, as well as integrate with the company’s main software platforms.

      We combined our extensive FMCG and RGM expertise to map out a three-year migration journey for changing processes, people, data and software tools. The ultimate goal was access to better-quality data insights that enabled faster, more informed responses to growth opportunities. To date, the RGM tool has been successfully rolled out to 12 of the company’s markets and we continue to add to and enhance its functionality.

      Stephen Greiff

      Director

      KPMG in the UK


      This highly impactful ‘one-stop-shop’ for the company’s RGM function enables a transition from being relatively light on data and analytics, with a short-term sales support focus, to having a broader outlook on its revenue generation.

      What this gave our client:

      • Time-saving automation of RGM analytics.
      • Better decision-making on product pricing and promotions.
      • Improved product mix and pack architecture across brands and markets.
      • More accurate analysis of investment with retailers.

      Our ‘always on’ RGM analytics tool has helped the frozen food company to deliver a 6.1% CAGR in gross margin over the last two years (2023 and 2024).



      Understanding the client’s challenges

      The ‘FM’ in ‘FMCG’ means businesses in the sector must respond quickly to seize business opportunities. For a UK-headquartered European frozen food company with a large portfolio of brands, that’s a sizeable challenge. It operates across 22 European markets and constantly juggles large volumes of product and market data.

      However, the company’s teams responsible for managing revenue lacked consistent and continuous access to timely data insights. Inevitably, this meant ad hoc decision-making and duplication of effort.

      Consequently, it hindered optimal commercial decisions relating to key aspects of revenue management, including:

      • Product pricing
      • Product promotions
      • Profit mix across its brands and packs
      • Investment with retailers who sell its products

      KPMG began supporting the company on a project to address the challenge that began in post-covid world. We identified three challenges to overcome:

      • Getting everybody aligned on what they wanted in the ‘front end’ of an RGM solution.
      • Agreeing a roadmap internally that could be aligned across multiple markets and brands.
      • Aligning the entire group, cluster and market teams to create a ‘one-stop-shop’ RGM solution.

      Creating the right RGM solution

      The client’s goal was to integrate a new RGM function into its operations and determine how to plug in higher-quality insights and planning into the company’s business process. The solution had to enable data analytics to be automatically provisioned with self-building analyses rather than having teams manually compile data in Excel. This would prevent the inefficient ‘cottage industry’ of spreadsheets where different people might get different results based on their individual data handling decisions.

      A significant challenge was to migrate the reactive net revenue management team into an RGM team where dozens of staff would be using the tool daily and monthly.

      The change meant evolving from a relatively data-light, short-term sales support function to stepping up the scope, professionalisation and capabilities of that function. KPMG’s solution had to work in a format acceptable to current SAP Analytics Cloud (SAC) users.

      We mapped out what the RGM team needed to achieve agreeing with the client:

      • What resources were needed?
      • What market processes were required?
      • How to power those processes with data and analytics?

      The firm then wrote out the processes and identified the supporting data and analyses needed to drive them within strategic and annual business planning activities. Based on this information, KPMG was able to scope out the recommended solution.

      For this, the firm:

      • Defined the company’s data requirements.
      • Identified data sources and metrics.
      • Developed Key Performance Indicators, calculations and parameters for the agreed technology solution.

      Addressing the challenges end-to-end

      For the solution, we created an end-to-end integrated tool featuring:


      warehouse

      A data warehouse

      Our team defined data requirements by gaining a detailed understanding of the data landscape for two of the company’s largest representative markets. Then, the firm integrated multiple data sources into a single data warehouse, from which individual data products could be created to drive the data science models and the SAC data models required for visualisations. This enabled automatic data refreshes for each market.

      data_exploration

      A data science engine

      We built a statistical modelling software engine for analysing data inputs. This included price elasticities calculations and product promotion effectiveness calculations. The engine also provides outputs that can be used in predictive scenario models, so the impact of different RGM decisions on sales and margin can be tested.

      insights

      Front-end visualisations to deliver key insights that enable tactical and strategic decision-making

      For the new RGM tool to gain immediate traction with the company’s staff, it had to be as user-friendly as possible. We visualised the analyses for users as ‘pages’, each of which answered key business questions, within SAC ‘stories’. Each ‘story’ related to one of the RGM levers, with which the users are familiar, such as mix, pricing, promotions, trade terms and pack price architecture. To smooth the technical handover, this was built in an already well-established technology stack that included Google Cloud Platform (GCP), SAC and Microsoft SharePoint.

      Pilot testing and rollout

      Strong project governance underpinned the project. Careful review discussions took place at key stages up to and during the pilot and rollout stages. Our overall approach was to ‘work backwards’, first by determining what inputs were required by users and then what outputs should be generated.


      • User acceptance

        We ran the pilot of the processes and analytical approaches before refining them so they could be used as part of the input to the design of the RGM tool. Using information gathered from the pilot, user acceptance testing enabled essential feedback on technical issues and design considerations to be highlighted to the company’s RGM leadership team.

         

        Importantly, responses were obtained from future users across four of the company’s key markets and communicated to all stakeholders on the project so they could see how their input was used to improve the RGM tool. Also, it meant there would be no surprises when the RGM tool was rolled out to different markets.

      • Focus on data analysis capabilities

        Our team was acutely aware that on a project like this, ‘the devil is in the detail’. Getting the backend data model, data engineering and key performance indicator (KPI) calculations right was vital. To ensure this, the firm worked closely with the company’s Data Office, which managed the provisioning of the initial data sets that kicked off the data pipeline for the tool. Weekly meetings with the Data Office were an opportunity for us to explain our methods and to brainstorm with the client on how to improve efficiency in the use of data.

         

        For data science activities like price elasticity and promotional activities, we took business stakeholders through each step very carefully, particularly in explaining market-level capabilities to adjust model parameters. The firm created monitoring reporting for central business users to manage market-level adjustments and ensure that the outputs remained within expectations.

      • Building a repeatable tool

        Once the RGM tool had been proven and accepted by the user acceptance tests and RGM leadership, our next task was to expand the scope of the tool across further markets. For this crucial phase, the firm worked with the company’s main RGM team, the Data Office and IT teams to understand any data differences and gaps across markets and to build a collaborative plan to address them.


      The outcome

      By September 2024, we had supported in rolling out the core RGM product with a price elasticity component to 12 markets. A promotional source of volume component is currently in five markets, with plans to expand to another five or six markets, depending on the final agreed scope.

      What this gave our client:

      • Time-saving automation

        The RGM tool enables automatic revenue growth management analytics and drive enhanced consistency in pricing, promotions and product management across all its markets.

      • Better decision-making on product pricing

        The RGM team now makes pricing decisions, particularly on promotions, using analytics that inform them how much to discount products, how much display space in stores to buy from retailers, how often and when to run promotions, and whether to run promotions together or separately.

      • Improved product mix

        An important consideration is mix and assortment management. By better understanding across all products where it makes the most money and how products are performing, the RGM team knows where to increase or decrease support, for example, on marketing, in-store or promotional support.

      • Enhanced trade investment analysis

        Trade investment relates to margins agreed with retailers, which are usually negotiable. The company can leverage RGM data in their discussions with retailers around margins, promotions, product positioning, etc. This is helping to strengthen customer relationships. Previously, this activity was done piecemeal and not for all brands. Now, comprehensive trade investment analysis is available across brands in a process that can be applied consistently.

      • Delivered a 6.1% CAGR

        The RGM tool’s ‘always on’ analytics support revenue growth management decisions and has helped to deliver a 6.1% CAGR in gross margin over the last two years. This is also reflected in a 190 basis points of improvement in their gross margin over that period.


      Success through collaboration

      We worked closely with teams based in its largest markets, notably the UK, France, Germany and Italy, to create a strong understanding of the client’s requirements. This was applied across all of the company’s brands. The collaborative approach meant that we drew on significant market input to design the RGM tool.

      In particular, the firm built a strong working relationship with the Data Office team. Gradually, reticence about sharing sensitive feedback evolved into a collaborative problem-solving effort. Both sides brainstormed solutions together in a classic ‘forming, storming, norming’ progression.

      We ran initial training workshops for the RGM group and market super-users before the company used its own training resources to handle the bulk of the training workload. The firm also created extensive technical documentation for the work carried out in both GCP and SAC. We then ran multiple technical hand-over sessions to the company’s IT support team so they could successfully take on the support of the tool ‘in-house’.

      Pooling resources to deliver the required outcomes

      We brought an objective perspective to the project thanks to its extensive experience working in the FMCG sector. The team also provided extensive expertise in building similar RGM tools in other sectors, including medical wholesalers, retailers and manufacturers.

      The firm pulled in technical expertise from its Central SAP team in India and its Google Cloud team for technical support. Knowledge was pooled and tailored to meet the company’s RGM goal.


      We’ve transformed our RGM capability over the past couple of years. KPMG has been an essential delivery partner throughout this journey. They took the time to learn our organisation and culture and built strong relationships with our group commercial team, stakeholders in the markets and colleagues in the Data Office. KPMG delivered this ambitious implementation at speed, went the extra mile to keep the project on-track and maintained a real sense of partnership, even when things got tough. The work has earned the team a lot of kudos. Launching Wave-1 on time was crucial. We even got a text from the CEO saying “Congratulations”! This effort is yielding significant business results. RGM is the #1 profit driver in the plan over the past two years, where we have delivered a 6.1% CAGR in gross margin, while more than offsetting cost inflation.

      Group Head of Revenue Growth Management Insights and Analytics



      The only way isn't up

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      Our people

      Stephen Greiff

      Director

      KPMG in the UK

      Shashank Dewan

      Partner, Deal Advisory

      KPMG in the UK


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