From Siri answering your questions to predictive analytics anticipating product defects, smart apps seem to be cropping up everywhere. Developing these smart apps are at the top of every business’s to-do list for 2017. While it is good news for data scientists who will be in demand because they have the specialized expertise to build and maintain these complex applications, it also gives them an opportunity to evolve their role into more of a strategic business partner.

Companies are betting their businesses on the development and deployment of these apps, giving them the starring role in their product roadmaps and sales strategies. And, it won’t be too far off, when smart apps will be a requirement for any company that wants to remain competitive in its marketplace.  It won’t be enough for software to “do.”  It will be required to “think and suggest.”

This smart apps explosion can mean big changes for data scientists, requiring them to shift their perspective – to think as rigorously about the business requirements as they do the technical ones. Here are key areas that data scientists need to consider as they change their perspective to the business mindset:

Consider your objectives

What business problem are you trying to solve? For example, if you’re developing a chatbot, do you want to improve customer service, brand recognition or sales?  Once you determine the key business problem, you can more effectively develop an app, and aggregate and correlate the data to address the problem. 

It’s also important to think about how much time and focus you allot to solving the problem. Applying the 80/20 rule where roughly 80 percent of your results come from 20 percent of your efforts, it makes sense to spend 80 percent of your time on 20 percent of the most important applications.  For example, if you are developing a smart app for a medical device, you probably need to spend more time striving for a 99 percent accuracy rate, and continually work on it until you get there. But if you’re designing a chatbot to speak with customers during the sales process, having it understand speech 80 percent of the time will probably do the trick.

While it’s hard for scientific-driven professionals to pull back from perfection, it is often the right thing to do from a business perspective.  If you are laser focused on developing that perfect app when perfection isn’t necessary, you are taking away time from other development initiatives.

Can you get creative with the data?

After you determine which type of data you need, you need to figure out where to find it and how to access it.  It’s bound to be captured somewhere in your organization, including in log files or through IoT sensors. Now, IoT devices make different types of data available from new sources, opening up new possibilities of data sources, such as temperature, humidity, movement, etc.  Live in the data, understand what it represents and what you can do with it. Get creative with the type of data you could collect and see how it correlates with the accuracy of your models.

You also have an opportunity to think beyond the questions that are being posed, and identify other questions or issues you should consider. For example, you might notice that a manufacturing plant has the greatest number of errors on Tuesday and you want to determine why. Perhaps the machine operators have to work a longer shift on Mondays and are more tired on Tuesdays, or maybe there is another reason. By thinking beyond the questions you have, you can uncover other problems or opportunities and bring more value to the business.

Don’t be a purist for purity sake

Today, there are a variety of advanced tools, such as Microsoft Azure, Google Cloud Platform and IBM Watson, that can help you build complex smart apps faster. For example, using these tools you might be able to build 10 algorithms in the time it takes you to build five manually, giving you more alternatives to find the optimal data model. These cognitive tools are the future of AI, and because they provide a ready-made foundation, you don’t have to build a solution from scratch, freeing you up to focus on solving business problems.

In today’s ubiquitous smart app environment, data scientists are at an important crossroads where they can expand their role to encompass more business strategy. The more that you immerse yourself in a business mindset to complement your technical one, the smarter smart apps you can develop – and the greater value you can deliver to your organization. 

(About the author: Carlos Meléndez is chief operating officer at Wovenware, a nearshore provider of smart software solutions located in Puerto Rico. Carlos can be reached at Carlos cmelendez@wovenware.com or 787-525-5372.)

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