The Impact Data Scientists Can Make on Your Business

data scientist

Data. Four letters, a global impact – with the rise of digital technologies, it becomes important for businesses to ask, how can they leverage the data they create to improve their business operations?

From simple sensors to complex algorithms, data forms the backbone of today’s digital economy. As a result, it can yield impressive cost benefits when data is correctly interpreted, understood and actioned in the workplace – a recent survey by McKinsey & Company found that data reporting can not only increase sales, but assist in optimising supply chains and reducing operating costs.

Let’s explore data, what it can mean for businesses, and how a master in data science online may be helpful in learning more about what – data can do for your business.

Data – An Untapped Potential

You may not realise it, but as individuals, we generate a lot of data on a day-to-day basis. The smartphones we use may generate location data, the web browsers we utilise store cookies, and the pictures we take store vital information in the form of EXIF data.

That’s not all, though – the data that’s collected can vary from whitegoods temperature monitors to the complex sensors on aircraft. In fact, it’s estimated that more 2.5 exabytes of data are generated on a daily basis, which is a massive amount of data for any individual business to handle.

How Can Data Be Used In Business?

Data scientists have the capacity to use complex data sources in a number of ways. By being data-literate, and having the capacity to communicate the complex needs of data with stakeholders, design and implement solutions, the role of the data scientist has become a position that falls hand in hand with using data in a business.

Some strategies that may be used in data may include strategies such as:

  • Machine learning (ML): using advanced computer models to build algorithms and systems that can adapt to different types of data coming into a workplace. For example, this may involve using image recognition to gather data on the characteristics of both a company’s products and those of their competitors.
  • Artificial intelligence (AI): using internal data to improve processes within a workplace. For example, using a history of past customer interactions, businesses may choose to develop innovative tools such as chatbots to provide assistance with customer queries, while minimising the wait that a customer may have to deal with a human operator.

Data In Practice: Domino’s Pizza

A contemporary example of the impact that data scientists can have on the operations of a business is through major pizza chain Domino’s Pizza. As a business, they faced a number of different problems. One of these included addressing quality concerns – there were a large number of complaints from customers about quality and consistency. 

As a business, Domino’s wanted to identify what problems were arising with pizza quality, while sifting through information about the tens of thousands of pizzas sold on a daily basis. By identifying the issues faced, then they could provide some simple changes that could be worked into the pizza-making process – improving the quality of pizza delivered to customers.

Domino’s solution to the quality problem? An innovative AI solution known as the DOM Pizza Checker. Rolled out in every store, the pizza checker is used as a hardware tool, sitting above the pizza cutter. An optical device then scans the pizza, addressing issues such as:

  • Identifying quality and cleanliness issues that may be faced.
  • Displaying an image of the pizza for a customer to view as it’s being delivered.
  • Analysing pizzas that are produced, to determine whether the pizza has been produced correctly (for example, cheese spread, pizza temperature, topping distribution).

By using the data available to Domino’s, they were able to improve customer feedback, as well as identify potential issues in the pizza manufacturing chain. After a small period of time, quality scores improved dramatically, leading to improved customer satisfaction scores.

Domino’s was able to take the successes with the pizza checker and use the data science lessons learned to improve other aspects of the business. The impact of data scientists at Domino’s has allowed for improvements within other areas of the business, such as marketing and customer rostering.

The role of the data scientist is constantly evolving, and we’re only just starting to see the results emerge from modern data science strategies. If you’re looking to challenge yourself, it may be time to consider a career in data science.

Related: 3 Ways Data Science is Being Used in Ecommerce

Cover Image by Storyset

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