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1 R O I C A S E S T U D Y P R O G R A M : E N T E R P R I S E A P P L I C A T I O N S D O C U M E N T R 1 08 J U N E MICROSOFT RENAULT SPORT FORMULA ONE TEAM A N A L Y S T Rebecca Wettemann T H E B O T T O M L I N E Renault Sport Formula One Team deployed Microsoft Dynamics 365, Power BI, and Azure Machine Learning to support its racing car development processes. Nucleus found that moving to the cloud enabled the team to automate processes and combine disparate data sources to drive greater visibility and productivity and improve team performance. ROI: 913% Payback: 5 weeks Average annual benefit: $2,733,750 T H E C O M P A N Y Renault has been associated with Formula One racing since 1977, both as a constructor and engine supplier. The current Renault Sport Formula One Team was formed with the purchase of the Lotus F1 team in December Based in Enstone, UK, the team is currently competing in the 2017 Formula One season, but over the years the team has collected more than 160 wins as engine supplier, ranking third in Formula One history. Team sponsors include Bell & Ross, Devialet, Genii Capital, Infiniti, BP, CD-adapco, Microsoft, Pirelli, and OZ Racing. T H E C H A L L E N G E Formula One is a highly competitive and costly sport, with leading teams spending more than $300 million a year to compete in a series of roughly 20 races. Nucleus Research Inc. 100 State Street Boston, MA Phone:

2 Renault Sport Formula One Team, like others, develops and produces two cars over the course of the season, taking insights and data from each test, practice, qualifying, and race session to drive car improvements. The ability to digest large quantities of data for decision making is critical. With teams total budgets investments and budgets varying wildly, efficiencies gained by technology can be an important difference. With a rate of design, simulation, testing, and manufacturing that is much faster than traditional manufacturers, Formula One constructors need up-to-date cost tracking and visibility as well as global secure access (during racing season, the team is working in a different location roughly every two weeks). The team had historically used a highly-customized version of Sage Software and a number of custom applications to support its operations, and a combination of spreadsheets, SQL Server reporting services, and data extracts for analytics. The team found that the growing demands for real-time data analysis challenged its traditional on-premise systems and reporting tools to deliver what the team needed. In 2012 the team began to explore other technology options. Cost : Benefit Ratio 1 : 4.6 T H E S T R A T E G Y Renault Sport Formula One Team explored a number of options including SAP and Microsoft Dynamics for its core ERP and ultimately decided on Dynamics 365 for two main reasons: The team s business and operational model is different from other manufacturers. The team was comfortable that Dynamics 365 could be configured to support its business more easily than other options. Microsoft s extended development environment, including application programming interfaces (APIs) would enable the team to easily integrate it with other applications and data sources and support those integrations on an ongoing basis. The team started a phased deployment working with Microsoft professional services in 2012, beginning with moving its finance and some manufacturing operations from Sage to Dynamics 365. In 2013, it implemented a third-party project planning module, and in 2014 it completely migrated off of Sage. During that time, Microsoft had continued to advance its analytics and Azure Cloud offerings, and Renault Sport Copyright 2017 Nucleus Research, Inc. Reproduction in whole or in part without written permission is prohibited. 2

3 Formula One Team added Azure Machine Learning, Office 365, and PowerBI to its deployment. Today, users can access all the up-to-date data they need in one place whether they are on the road, at the track, or in the office. They also use Azure Machine Learning with simulator- generated data so they can determine how design changes will impact car performance before making changes to the physical car, instead of having to wait for new builds or use limited track testing time to gather data. TYPES OF BENEFITS Direct 7% 93% Indirect K E Y B E N E F I T A R E A S Moving to Microsoft Dynamics 365 has enabled Renault Sport Formula One Team to support its operational ERP needs and monitor costs at every level critical for a racing team with budget constraints. At the same time, the addition of Power BI and Azure Machine Learning has enabled the team to call up data in real time, analyze it with customized visualization and dashboards, and make decisions at the speed required to be more competitive. Key benefits of the project include: Improved operational efficiency and cost control. Before Dynamics 365, out-ofdate data made it difficult for managers to have a clear view of budgets and the impact of changes, and enabled staff to sometimes circumvent normal processes with limited accountability. The structure of Dynamics 365 enables the team to ensure that rules and processes are followed consistently particularly important in Formula One where teams can be penalized when they don t comply with very specific and constantly-changing F1 rules. Increased productivity. Because team members can access and input data from anywhere using mobile devices, and data from simulations and more than 200 sensors on the car itself are now immediately available, they spend less time finding and validating data and updating spreadsheets. For example, before every race or test, the team has to compile a report for shipping parts to and from the track so everything can be available and in place before the event. This process used to take weeks. It now takes a few hours. Improved data for decision making. The team can remotely send data and insights back to the design and manufacturing facility, and rapidly analyze that Copyright 2017 Nucleus Research, Inc. Reproduction in whole or in part without written permission is prohibited. 3

4 data using machine learning and Power BI, accelerating the time-to-decision and time-to-execution on new car design elements. CUMULATIVE NET BENEFIT 6,416,250 4,617,000 2,247,750 Year 1 Year 2 Year 3 K E Y C O S T A R E A S Key cost areas for the project included personnel time and software. Some initial licenses were already available as part of the team s enterprise agreement with Microsoft, and Microsoft provided some professional services as part of that broader agreement. B E S T P R A C T I C ES An important part of the use of Microsoft technologies at Renault Sport Formula One Team has been the ability to follow precise rules and processes while giving team members the ability to consume and input data with a high degree of flexibility. This drives a high level of accountability while providing greater visibility into each team member s contribution. C A L C U L A T I N G T H E R O I Nucleus quantified the initial and ongoing costs of the team s Microsoft investment over a 3-year period for this analysis. The costs represented are estimates of the actual costs incurred by Renault Sport Formula One Team and do not include the costs of software and professional services that were provided by Microsoft Copyright 2017 Nucleus Research, Inc. Reproduction in whole or in part without written permission is prohibited. 4

5 Dynamics as part of the existing enterprise agreement. Nucleus estimated the ROI based on the estimated value of those licenses and services at more than 300 percent. Direct benefits quantified included the eliminated Sage support costs and avoided IT resources to support data integration. Indirect benefits quantified included the increased productivity of team members, which was calculated based on the average annual fully loaded cost of an employee using a correction factor to account for the inefficient transfer of time between time saved and additional time worked. Not quantified were the additional indirect benefits of improved decision making and team performance, or the direct benefit of reducing manufacturing costs through more consistent and streamlined finance and manufacturing operations. Copyright 2017 Nucleus Research, Inc. Reproduction in whole or in part without written permission is prohibited. 5