Transforming Starbucks using Data Analytics | Big Data | AI | MBA Case study examples with solutions

have you ever thought there's got to be a better and simpler way to learn organizational strategies five minutes learning has a global and diverse collection of case studies to help

management students click the Subscribe button and hit the Bell icon to stay updated with our upcoming and interesting case studies Starbucks doesn't just sell beverages

all over the world it also collects a lot of data from over 100 million transactions per week what does it do with this information and how do artificial intelligence and

The Internet of Things play a role in this regardless of the size of your company Starbucks can be a great example of how to use data and modern technology to

gain a competitive advantage for example it is a Pioneer in combining loyalty Systems payment cards and mobile apps but that is only the tip of the iceberg

this video highlights five of the most interesting examples of how Starbucks uses data artificial intelligence and iot to gain a competitive advantage

Starbucks May no longer be a coffee company but rather a data technology company for food and beverages it's no secret that Starbucks is a

data-driven company it operates over 30 000 stores worldwide and processes nearly 100 million transactions per week this provides it with an in-depth

understanding of what its customers consume and enjoy it may surprise you to learn that Starbucks only started focusing on data

value a little more than a decade ago it wasn't that it hadn't used Data before a crisis prompted the company's transformation as with many major changes

in this case the change was prompted by the 2008 financial blip and subsequent store closures this taught Howard Schultz then CEO of

Starbucks that data should be used more analytically prior to that Starbucks like many other organizations made decisions based on experience and judgment

choosing the right location is critical to success in retail in 2007 and 2008 Starbucks CEO Howard Schultz was forced to come out of retirement to close

hundreds of stores and rethink the company's strategic growth plan this time Starbucks took a more disciplined data-driven approach to store openings

the company can choose the most strategic location for its new stores by using location-based analytics powered by Atlas a mapping and business

intelligence tool developed by esri before recommending a new store location Starbucks evaluates massive amounts of data including variables such as

population income levels traffic competitor presence and proximity to other Starbucks locations using this information the company can

forecast revenues profits and other aspects of economic performance for that location the software is also assisting in determining where the next 1500 Plus

stores should be located which will not only help the company expand but will also Drive revenue for new store developments Starbucks used the gathered data to

determine which products to offer when launching new products in particular when expanding its product lines into grocery stores the company

heavily relies on the data gathered according to a study 43 of tea drinkers avoid adding sugar Starbucks created a new product line of

unsweetened iced teas to cater to this Market also after discovering that 25 of consumers do not add milk to their coffee the company launched a new line

of black iced coffee without milk these menu enhancements and grocery store product launches are not only just providing customers with their favorite products they're also about convincing

their customers to avoid other coffee brands while at home it's a market share grab strategy that's been hugely successful it's a way for

Starbucks to take a retail brand and bring it into consumers homes when Starbucks launched its Rewards program and mobile app its data collection increased significantly

this allowed them to get to know their customers and extract information about their purchasing habits using its mobile app Starbucks collects data about what where and when its

members purchase coffee Starbucks uses the digital flywheel program a cloud-based artificial intelligence engine capable of making precise food and beverage

recommendations as a result even when people visit a new Starbucks location the store's point of sale system can identify the customer through their phone and give the Barista

their preferred order Starbucks could also suggest new products a customer might like based on their purchase history as well as provide unique discounts and rewards on

specific items based on their unique preferences Starbucks went one step further by collecting data on weather patterns and their relationship with customer order patterns

this enables the company to provide even more personalized experiences and promotions such as delivering cold drinks to a customer on hot days

one implication of the preceding examples is that Starbucks can constantly refine and adjust its offerings Starbucks data-driven approach allows it

to make changes based on customers location and time this has an impact on products promotions and pricing however if you're in store offerings are displayed on

printed menu boards above the counter there is a disconnect with the ability to constantly adjust things this is one of the reasons why retailers continue to favor low-tech Solutions

such as blackboards Starbucks on the other hand sees the solution as a rollout of digital signage in stores with computer-generated menu displays

this completes a chain that allows changes in the customer experience to be reflected in the store obviously this raises a slew of questions and there's plenty of room for

things to get complicated however as of mid-2018 Starbucks was only testing this in a few locations it concentrated its efforts on promoting

specific products based on local factors such as weather or time of day our final example as coffee machine maintenance and General in store machinery

the typical in-store Starbucks transaction is relatively low cost and short-lived a store success is dependent on high levels of customer throughput so when a

machine fails it can have a significant impact on business performance Starbucks doesn't keep Engineers on site for breakdowns instead they send them

out to deal with repairs and to perform planned maintenance having Engineers respond quickly to Broken machines makes a difference there are conventional approaches to this

problem this typically means collecting data about failures machine usage repairs required and so on regular data analytics as effective at

identifying Trends and patterns AI can assist in taking this to the next level by forecasting breakdowns and maintenance requirements Starbucks has taken a step forward by

developing a new coffee machine the cloverex currently this is only used in Flagship and concept stores it's not only Cutting Edge in terms of coffee making capability but it's also

Cloud connected this not only enables a more comprehensive collection of operational data it also enables remote fault diagnosis and even remote repairs

similar ideas will apply to other machines for example stores now have a standard oven that is also computer controlled to ensure consistent preparation of Hot Products around the

world however the current machines need to be updated by USB drive this occurs Whenever there is a change in machine configuration such as the

introduction of new products in the future this will undoubtedly become a direct Cloud connection opening up more AI opportunities

while Starbucks was not born in the digital era as a digitally native company it has successfully integrated new technologies into its Core Business

data analytics has unquestionably become the backbone of Starbucks continuous improvement over the years in the future Starbucks will continue to gather more data and apply it in even more

innovative ways to provide a more personalized customer experience and Achieve business excellence Starbucks as a textbook example of how to start a journey to utilize data

strategically implementing plans systematically and thoroughly another lesson is that artificial intelligence as part of Starbucks journey to learn how to use data using

artificial intelligence was not something that happened out of a burning desire it was just a matter of doing it when the time was right in each area thank you so much for listening to this

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