What McDonald’s $300M Acquisition Says About Data in Retail

This week, McDonald’s acquired a big data startup for $300 million this week. It’s common for Amazon and other ecommerce companies to purchase technology and continue licensing the service to others, but that’s not what happened here.

What did happen? One of the largest food companies in the world took a massive step towards becoming a big data technology leader by purchasing a data startup. They plan to use their new technology for the improvement of their own operations and their own customer experience.

McDonald’s believes that measuring their own operational and customer data is worth more than $300 million dollars. Let that sink in for a minute.

McDonalds’ acquisition is not a bet on where the world of commerce is going, but rather a highly intelligent reaction to the way commerce works today.

Machine learning (ML) and artificial intelligence (AI), which rely on big data to drive predictions and insights, are capturing very large business investments on a daily basis. IDC estimating that spending on machine learning and AI will increase from $19.1 billion in 2018 to $52.2 billion by 2021.

It’s clear that the market as a whole understands the value of unlocking their data in order to analyze and improve their revenues, efficiencies and bottom line. Now, the possibilities with big data are so huge, that even industries that are traditionally driven by branding and customer value, like retail and fast food, are seeing incredible value from the big data revolution.

The Impact of Big Data and Data Analysis in Retail

Data and technology are playing ever growing roles in business strategy, especially for enterprises that are competing in the highly-competitive retail and ecommerce sectors. Big Data is what separates the world’s most successful retailers and consumer goods companies from those that are gradually falling along the wayside.

When your customers can order from any business, anytime, anywhere, businesses need to work hard to stand out. The first step is to develop a customer-centric approach; to do that, you need big data.

Customer Centricity

McDonald’s investment is all about customer centricity, and being able to offer exceptional experiences with data.. They are taking their excellence in supply chain operations and their knack for customer service, both of which have made them the successful, famous brand that they are today – and digitizing it in order to reach the next level of success as a brand.

The goal is to stand out and offer a superior customer experience that increases revenues; the strategy is to power that customer experience with data. Full visibility into every step in the customer journey helps brands understand what their customers like, what they don’t, and what brands can do to improve their customer’s experience and, as a byproduct, improve conversion rates and build loyalty. That knowledge is a powerful differentiator that can help companies create a competitive edge in their market while improving their customers’ experiences.

Data-Driven Operational Efficiency

Similarly, when retailers gain visibility into their business and logistics operations, they can make accurate decisions about where, and how, to implement changes that will make an impact on operational efficiency and costs.

For restaurants and fast food chains, getting data about prep time is the first step in implementing tech solutions and gaining insights that can improve order fulfillment efficiency. If a restaurant chain collects data from its prep area and kitchen, they can get a better understanding of how long prep time takes. Machine learning, the backbone of which is data, can model prep time to provide more accurate predictions of how long prep time will take in the future.

That information is critical for a few reasons: food loses freshness the moment it’s finished preparation. If delivery providers can arrive on site exactly when the order is ready to go out, the meal can more quickly reach the end-customer, while still fresh. Also, by sending out deliveries the second orders are ready, instead of having drivers wait around for an order to be ready, you’ll keep your delivery drivers productive. The end result will not only be happier customers, and increased delivery capacity, but a reputation for reliability as a brand. That’s the power of big data

Data helps you do more, and do it better.

The New Rules:
Delivery Logistics in the Ecommerce Era

Reducing the Supply Chain Costs

Many business operations today, particularly supply chain operations, are black boxes – their inner workings are complete unknowns. Time is lost, efficiency is reduced, and expenses accumulate, but no one knows why or how.

Recognizing this shift, 72% of retailers are already in the process of digitizing their supply chain to enable real-time data reporting.

For example, companies often don’t know how long delivery providers spend on site – especially if they use a third-party logistics provider or external crowdsourced fleet. Understanding and accurately projecting time on site translates to companies taking the correct amount of time into consideration designing routes, and conserve resources which might otherwise be unnecessarily spent. Also, by planning routes based on accurate data about delivery times and time on site, companies ensure that as many deliveries are sent out as efficiently and cost-effectively as possible, while meeting promised delivery times.

Big data, and the insight and opportunities for optimization that it provides, has unlimited potential for retailers, grocers, restaurants, and any large enterprise with complex supply chains.

Why It's the Right Time for Data Analytics at Scale

If you’re thinking of adding data-driven solutions to your roadmap only in 2020, don’t wait – it may take years to reach actionable operational insights or improve your profit margins.

Big Data – in this case, the mountains of historical data that most companies have but don’t do much with – is the backbone of any technology solution that needs to recognize patterns and draw conclusions from them. But identifying which pain points need to be prioritized, and what data points to use in order to gain valuable insights into these pain points, all takes time.

Not every company is a McDonalds, and if you don’t have a quarter of a billion dollars at hand to buy the company that has the technology you want, developing a data analytics solution takes a great deal of time, money and human resources.

In a world of omnichannel retail, with sales happening online and offline in thousands of different locations, collecting and aggregating that fragmented data is a feat of enormous complexity. The data never stops coming, and can double every couple of months, so tools need to be put in place to deal with that overflow of information.

Now is the time to add data analytics to your short-term roadmap, and find out where it will make the most impact on your business. Start building POCs today, find where your ‘wins’ are, and expand on them. Look for tools to manage your data and solutions that help translate it into actionable insights that can transform your business operations.

For companies that don’t have the ability to buy a company or build an in-house solution, the good news is that data has become cheaper than ever to collect, automated, and utilize, and there are technologies that can help sort through it all. Through the use of automation technology, data management software, and data analytics, retailers can get insights that can have a significant impact on their bottom line by greatly improving efficiency, cutting operational and supply chain costs, and improving the customer experience.

Conclusion

McDonald’s investment is more than a story about an ‘AI powered personalization anywhere’ platform, as Dynamic Yield describes its solution. It’s a story about one of the largest food companies in the world recognizing the importance of data and ready to expand towards being a technology company in order to make use of it.

It’s a clear testament to the benefits of big data: better customer experiences, improved operational performance, and enhanced brand positioning. As technology continues to develop, one thing is certain: Data is here to stay.

Lior Sion

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