Business Basics for Data Scientists

The key metric we’re optimizing for is profit.

You reckon that to maximize profit, you can increase revenue, decrease costs, or both if you’re a magician.

Let’s talk about how your work with Machine Learning can influence either variable.

Superpower Machine LearningAs a Data Scientist, you’re blessed with the superpower of Machine Learning.

You feast on data and turn it into superhuman predictions to power mind-bending products.

Let’s explore how to use your power wisely, Luke.

⭐️Photo by Lopez Robin on UnsplashAndrew Ng, Founder of Landing.

ai and former Google and Baidu Brain Lead, states that Machine Learning generates value in three ways:Create new productsImprove existing productsAutomate processesLet’s go through examples for each category.

Create New ProductsMachine Learning helps your company create entirely new products to increase revenue.

An example is new mobility services powered by self-driving cars, also called Robo-Taxi.

Without Machine Learning, this new product is hard to create.

In this case, Machine Learning allows the company to develop an entirely new product to increase revenue.

The holy grail of Artificial Intelligence (“AI”)-powered products is a product that enters the Virtuous Circle of AI.

It all starts with a product that is already good without AI but continually improves with more users and more data.

Tesla is a good example.

A Tesla car is fun to drive without AI but constantly improves as more users collect data.

This makes the Tesla Autopilot ever more enjoyable.

Elon Musk, Tesla’s CEO, estimates that his company collects 99.

5% of all data from vehicles globally.

Ready, set, game for Tesla?Source: https://landing.

ai/ai-transformation-playbook/When looking for potential new products, you can do four things:Evaluate competitor product offerings.

Are they offering products that customers want and you could emulate through AI?Look to other industries.

Can you learn an interesting approach from this Chatbot AI company?Brainstorm new ideas.

Can you come up with a cool idea during a hackathon?Check your data.

Can you use this data to create a new AI product?Machine Learning increases profit by creating new products, thus increasing revenue.

You can also improve existing products with your superpowers.

Improve existing productsSince your company exists, it has a product or service that it’s selling.

Popular item recommender from is24.

de for new usersIf you work in a digital business, chances are that a recommender system exists.

In the example above, you see a popular item recommender by Germany’s leading real estate site.

It recommends houses in Sweden to me – it’s not relevant to me.

Many companies still use popular item recommenders.

These sweet and silly algorithms show which products have been most frequently bought from your company.

With Machine Learning, you can build a nifty algorithm that offers customized recommendations.

Talk to Product Managers directly to find out how to improve existing products.

You have the knowledge about Machine Learning, they know their product inside out.

They know about its challenges and roadmap ahead.

Together, you will come up with a great way to improve an existing product.

You’ve seen how to increase revenue by creating new or improving existing products with Machine Learning.

Yet Machine Learning can also drive down costs.

Let’s find out how next.

Automate ProcessesMachine Learning reduces costs by automating processes.

Every company has costs to create products.

Machine Learning tasks like computer vision or natural language understanding support processes perfectly.

The larger the company grows, the higher the potential for repetitive tasks that can be automated.

This is often referred to as Robotic process Automation, RPA.

Automating dancing.

So helpful.

A good example of using RPA to decrease costs is automating visual inspection in manufacturing.

Visual inspection is the process of inspecting produced goods with your eyes.

Imagine a team of people checking if newly produced cars have any scratches on the exterior.

Audi automated this process by using computer vision.

Landing.

ai is an entire company focusing on that task.

Visual inspection of a manufactured good.

To identify tasks for process automation, look for repetitive tasks which need limited cognitive capacity.

Andrew Ng gives the rule of thumb that anything that takes a human less than a second to do, can probably be automated.

This way you can decrease costs and impact the profitability of your company.

This is a great example of decreasing costs through automating processes.

Now that we know how to impact profit through Machine Learning, let’s prioritize the search for your next project.

Applying the Fundamental Business EquationManagement Consultants focus on increasing revenue before decreasing costs.

Decreasing costs can cause unintended consequences on the quality of existing products.

This leads to lowered revenue again.

Revenue before Costs.

 — Harvard Business ReviewPhoto by Franki Chamaki on UnsplashPlus, it’s more fun to come up with great new products.

This idea holds for non-profit and governmental organizations as well.

Thus, the general advice is to increase revenue before decreasing costs.

Key TakeawaysAs a Data Scientist, you get paid to optimize your companies’ performance towards profit.

You know how you can impact profit by increasing revenue or decreasing costs.

You’ve gotten this far, now save the juice for work.

Photo by Roman Kraft on UnsplashOptimize towards profitProfit = Revenue — CostsRevenue before costsIncrease revenue by creating new products or improve existing onesDecrease costs by automating tasksNext, use the AI Project Canvas to pitch your idea with an impact on profit to management.

This post continues the ongoing series of educating Data Scientists to become business-savvy.

The series aims at helping you polish your overall Data Scientist skill set.

If you enjoy the format, please follow me on LinkedIn or Medium to stay up to date with new articles.

Photo by Miguel Bruna on Unsplash.

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