Reskill, not Replace: Use Data Science Training to Take Employees to the Next Level

There currently exists a notable shortage of Data Scientists and analytical and managerial talent across all the industries, and hiring external Data Scientists is difficult, expensive, and ineffective. At the same time, it is important to be skilled in Data Science as companies need Data Scientists’ expertise to be able to interpret and analyze the large amount of data that they work with on a daily basis, which according to an article published by EDUCBA is what helps them achieve their long-term goals and objectives. 


“If a firm chooses not to retrain, it replaces existing employees with new ones. In the process, social networks in the workplace are disrupted, and social capital is destroyed. If a firm does retrain, it preserves social networks and retains social capital.” — Wharton Management Professor Peter Cappelli. 

The solution to this problem is to effectively train your employees in Data Processing and Analysis internally so that they are ready to transform your company into one that can compete in today’s tech-savvy market. Korbit has partnered with Data Scientist and Data Science Ambassador Katherine Munro and Larochelle’s Analytics Manager Charles Saulnier to discover the importance of Data Science and AI, and enlighten the audience with how you can train your employees effectively. 

 

Identify biases: Achieve better quality results  

Operating on incorrect or low-quality data can be deteriorative to a business’ operations. Not only will this pivot the company in the wrong direction and have them distracted by the wrong things, but it will keep them uninformed and disadvantaged compared to their competitors. Charles Saulnier underlines the importance of Data Science in that sense. “Having statistical grounds will help you identify if there is bias in your data, and it will help you correct it by having a better picture of what you’re looking at,” explained Saulnier. With this feature, businesses will be able to identify biases in literature and data and produce and disseminate better quality results. This is important in today’s world, considering the abundance of misinformation driven by low-quality data and methodology. 

 

Data Science and AI knows your customers better

Now let’s look more closely at how Data Science and AI can dramatically transform an industry through the ever-growing field of e-commerce. Katherine Munro highlights the significance that the two fields have had in the flourishing of e-commerce through the multiple real-world solutions that they offer. Companies can now appeal to their consumers and fiercely compete in the market thanks to dynamic pricing, efficiently running operations through inventory management, intricately connecting with their customers through predictive marketing, and improving their product through accurate attribution. Munro goes into even greater detail here in one of our webinars!

 

Munro revealed the magic machine learning has had on product development through ML driven customer behaviour prediction. Employees trained in Data Science can now use this innovation to understand the customer type on a very granular level, classifying them not just by age but also by profession, interests, and price sensitivity. This leads to the evolution of a product that fits the consumer’s taste to a tee, increasing sales and customer satisfaction. 

 

Another striking example of a solution presented by AI’s revolutionary field is optimized emails and personalized messaging. “We all remember when we used to travel right?” Munro asked the audience, “we would book a flight, and afterward, we would get a personalized email from Trip Advisor on the list of things to do and the most popular activities in the destination.” This feature, along with time-optimized emails, leaves the consumer with the “positive feeling of a personalized text,” increasing their loyalty to the business as they become more and more engaged.

 

Interactivity and projects create optimal training result 

While this all sounds incredible, companies need to find the right way to train their employees in data science to have the best results. It’s not enough to introduce a one-size-fits-all program and expect all your employees to be knowledgeable in the field in a specific timeframe. “The ideal program would be able to reach your employees at their current level,” said Saulnier, “having the ability to segment your audience and provide multiple tracks and skills for them would be one of the key factors for adoption in the training program.” 

 

Saulnier also stressed the importance of an engaging curriculum to help keep the employees motivated to learn. The gamification of a learning platform is emerging as one way of achieving that goal. This feature allows the employees to look forward to learning and retaining the information they acquired. It psychologically shifts their conception of education from a concept that might be boring and repetitive to something that’s fun, engaging, and interactive. 

 

A final key point that both experts have agreed on is having employees develop the ability to apply the skills they have learned through the training program in a real-world setting. Saulnier phrases it as “striking the balance between theory and field projects,” while Munro advances it as “supporting the employees to work on real projects with real-world data.” This is crucial as employees need to translate the skills and knowledge they have learned into the real world to gain the appropriate experience to apply theory into practice. 

 

Interested in developing a personalized curriculum for your employees to enrich and advance their Data Science & AI skills? Take a Korbit’s customized data science course today!

 

[Text: Huda Hafez]

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