3 Ways McDonald’s France is Preparing their Data for the Future

Data access is one of the biggest influences on business intelligence, innovation, and strategy to come out of digital modernization. Now that so much data is available, the competitive edge for any business is derived from understanding and applying it meaningfully. McDonald’s France is gaining business-changing insights after migrating to a data lake, but it’s not just fast food that can benefit. Regardless of your industry, gaining visibility into and governance around your data is the first step for what’s next.

1. No More Manual Legacy Tools

Businesses continuing to rely on spreadsheets and legacy tools that require manual processes are putting in a lot more than they’re getting out. Not only are these outdated methods long, tedious, subject to human error, and expensive in both time and resources – but there’s a high probability the information is incomplete or inaccurate. Data-based decision making is powerful, however, without a data platform, a strong strategy, automation, and governance, you can’t easily or confidently implement takeaways.

Business analysts at McDonald’s France historically relied on Excel-based modeling to understand their data. Since partnering with 2nd Watch, they’ve been able to take advantage of big data analytics by leveraging a data lake and data platform. Architected from data strategy and ingestion, to management and pipeline integration, the platform provides business intelligence, data science, and self-service analytics. Now, McDonald’s France can rely on their data with certainty.

2. Granular Insights Become Opportunities for Smart Optimization

Once intuitive solutions for understanding your data are implemented, you gain finite visibility into your business. Since completing the transition from data warehouse to data lake, McDonald’s France has new means to integrate and analyze data at the transaction level. Aggregate information from locations worldwide provides McDonald’s with actionable takeaways.

For instance, after establishing the McDonald’s France data lake, one of the organization’s initial projects focused on speed of service and order fulfilment. Speed of service encompasses both food preparation time and time spent talking to customers in restaurants, drive-thrus, and on the online application. Order fulfilment is the time it takes to serve a customer – from when the order is placed to when it’s delivered. With transaction-level purchase data available, business analysts can deliver specific insights into each contributing factor of both processes. Maybe prep time is taking too long because restaurants need updated equipment, or the online app is confusing and user experience needs improvement. Perhaps the menu isn’t displayed intuitively and it’s adding unnecessary time to speed of service.

Multiple optimization points provide more opportunity to test improvements, scale successes, apply widespread change, fail fast, and move ahead quickly and cost-effectively. Organizations that make use of data modernization can evolve with agility to changing customer behaviors, preferences, and trends. Understanding these elements empowers businesses to deliver a positive overall experience throughout their customer journey – thereby impacting brand loyalty and overall profit potential.

3. Machine Learning, Artificial Intelligence, and Data Science

Clean data is absolutely essential for utilizing machine learning (ML), artificial intelligence (AI), and data science to conserve resources, lower costs, enable customers and users, and increase profits. Leveraging data for computers to make human-like decisions is no longer a thing of the future, but of the present. In fact, 78% of companies have already deployed ML, and 90% of them have made more money as a result.

McDonald’s France identifies opportunity as the most important outcome of migrating to a data lake and strategizing on a data platform. Now that a wealth of data is not only accessible, but organized and informative, McDonald’s looks forward to ML implementation in the foreseeable future. Unobstructed data visibility allows organizations in any industry to predict the next best product, execute on new best practices ahead of the competition, tailor customer experience, speed up services and returns, and on, and on. We may not know the boundaries of AI, but the possibilities are growing exponentially.

Now it’s Time to Start Preparing Your Data

Organizations worldwide are revolutionizing their customer experience based on data they already collect. Now is the time to look at your data and use it to reach new goals. 2nd Watch Data and Analytics Services uses a five-step process to build a modern data management platform with strategy to ingest all your business data and manage the data in the best fit database. Contact Us to take the next step in preparing your data for the future.

-Ian Willoughby, Chief Architect and Vice President

Listen to the McDonald’s team talk about this project on the 2nd Watch Cloud Crunch podcast.

McDonald’s France Gains Business-Changing Insights from New Data Lake

McDonald’s is famous for cheeseburgers and fries, but with 1.5 million customers a day, and each transaction producing 20 to 30 data points, it has also become a technology organization. With the overarching goal to improve customer experience, and as a byproduct increase conversion and brand loyalty, McDonald’s France partnered with 2nd Watch to build a data lake on AWS.

Customer Priorities Require Industry Shifts

As is common in many industries today, the fast-food industry has shifted from a transaction centric view to a customer centric view. The emphasis is no longer on customer satisfaction, but on customer experience. It’s this variable that impacts conversion rate and instills loyalty. Consequently, McDonald’s wanted to build a complete perspective of a customer’s lifetime value, with visibility into each step of their journey. Understanding likes and dislikes based on data would give McDonald’s the opportunity to improve experience at a variety of intersections across global locations.

McDonald’s is a behemoth in its size, multi-national reach, and the abundance of data it collects. Making sense of that data required a new way of storing and manipulating it, with flexibility and scalability. The technology necessary to accomplish McDonald’s data goals has significantly reduced in cost, while increasing in efficiency – key catalysts for initiating the project within McDonald’s groups, gaining buy-in from key stakeholders, and engaging quickly.

From Datacenter to Data Lake

To meet its data collection and analysis needs, McDonald’s France needed a fault-tolerant data platform equipped with data processing architecture and a loosely coupled distribution system. But, the McDonald’s team needed to focus on data insights rather than data infrastructure, so they partnered with 2nd Watch to move from a traditional data warehouse to a data lake, allowing them to reduce the effort required to analyze or process data sets for different properties and applications.

During the process, McDonald’s emphasized the importance of ongoing data collection from anywhere and everywhere across their many data sources. From revenue numbers and operational statistics to social media streams, kitchen management systems, commercial, regional, and structural data – they wanted everything stored for potential future use. Historical data will help to establish benchmarks, forecast sales projections, and understand customer behavior over time.

The Data Challenges We Expect…And More

With so much data available, and the goal of improving customer experience as motivation, McDonald’s France wanted to prioritize three types of data – sales, speed of service, and customer experience. Targeting specific sets of data helps to reduce the data inconsistencies every organization faces in a data project. While collecting, aggregating, and cleaning data is a huge feat on its own, McDonald’s France also had to navigate a high level of complexity.

As an omnichannel restaurant, McDonald’s juggles information from point of sales systems with sales happening online, offline, and across dozens of different locations. Data sources include multiple data vendors, mobile apps, loyalty programs, customer relationship management (CRM) tools, and other digital interfaces. Combined in one digital ecosystem, this data is the force that drives the entire customer journey. Once it’s all there, the challenge is to find the link for any given customer that transforms the puzzle into a holistic picture.

Endless Opportunities for the Future

McDonald’s France now has visibility into speed of service with a dedicated dashboard and can analyze and provide syntheses of that data. National teams can make data-based, accurate decisions using the dashboard and implement logistical changes in operations. They’re able to impact operational efficiency using knowledge around prep time to influence fulfilment.

The data lake was successful in showing the organization where it was losing opportunities by not taking advantage of the data it had. McDonald’s also proved it was possible, affordable, and advantageous to invest in data. While their data journey has only begun, these initial steps opened the door to new data usage possibilities. The models established by McDonald’s France will be used as an example to expand data investments throughout the McDonald’s corporation.

If your organization is facing a similar of issue of too much data and not enough insight, 2nd Watch can help. Our data and analytics solutions help businesses make better decisions, faster, with a modern data stack in the cloud. Contact Us to start talking about the tools and strategies necessary to reach your goals.

-Ian Willoughby, Chief Architect and Vice President

Listen to the McDonald’s team talk about this project on the 2nd Watch Cloud Crunch podcast.

Podcast: Cisco Cloud Unfiltered – Half a Million SKUs and Counting

How do you make the right decisions about moving to the cloud when there are over half a million SKUs in AWS alone? In this week’s episode of the Cloud Unfiltered podcast, Ali Amagasu and Pete Johnson talk with Jeff Aden of 2nd Watch about how AWS has changed, how moving to the cloud is helping some companies save a LOT of money, and where the cost savings opportunities are for others that haven’t made the move yet.Check it out:Hosted by Ali Amagasu and Pete Johnson, Cisco Cloud Unfiltered is a series of interviews with the people that are working to move cloud technology and implementation forward.

The Cloudcast Podcast with Jeff Aden, Co-Founder and EVP at 2nd Watch

The Cloudcast’s Aaron and Brian talk with Jeff Aden, Co-Founder and EVP at 2nd Watch, about the evolution of 2nd Watch as a Cloud Integrator as AWS has grown and shifted its focus from startups to enterprise customers. Listen to the podcast at http://www.thecloudcast.net/2019/02/evolution-of-public-cloud-integrator.html.

Topic 1 – Welcome to the show Jeff. Tell us about your background, the founding of 2nd Watch, and how the company has evolved over the last few years.

Topic 2 – We got to know 2nd Watch at one of the first AWS re:Invent shows, as they had one of the largest booths on the floor. At the time, they were listed as one of AWS’s best partners. Today, 2nd Watch provides management tools, migration tools, and systems-integration capabilities. How does 2nd Watch think of themselves?

Topic 3 –  What are the concerns of your customers today, and how does 2nd Watch think about matching customer demands and the types of tools/services/capabilities that you provide today?

Topic 4 – We’d like to pick your brain about the usage and insights you’re seeing from your customers’ usage of AWS. It’s mentioned that 100% are using DynamoDB, 53% are using Elastic Kubernetes, and a fast growing section is using things likes Athena, Glue and Sagemaker. What are some of the types of applications that you’re seeing customer build that leverage these new models? 

Topic 5 – With technologies like Outpost being announced, after so many years of AWS saying “Cloud or legacy Data Center,” how do you see this impacting the thought process of customers or potential customers?