With the rise of the internet, portable communication devices, and the application of artificial intelligence in our everyday lives, we’re witnessing some impressive leaps in technology. Arguably, the biggest since the dawn of time.
But the thing with such rapid progress is that, without the right strategies, it can quickly become pointless. And, if you’re a business owner, it can turn into a pretty expensive mistake as well.
It is for this reason that using data is so crucial for research and development. For one, it’s an excellent way to follow trends and market demands that will be relevant in the future. Secondly, it’s both an alternative and supportive input to speculative design. As such, using data can be the key to recognizing and solving humanity’s leading challenges in the years to come. We’re talking about everything from water shortage, climate change, the need to develop safe self-driving cars, and so on.
The Benefits of Using Data for Research & Development
From a purely business perspective, using big data in R&D has several important benefits.
For one, it’s an effective way to save both time and money. Particularly so when using already available information or investing in the continuous collection and analysis of data.
Secondly, it’s a more accurate way to collect, interpret, and apply information. Well-made collection systems allow businesses to gain access to more relevant data. McKinsey, for example, emphasizes the potential of big data in the healthcare and pharmaceutical industries. It states that big data allows for:
more streamlined clinical trial enrollmentreal-time data collection (and reaction, when necessary)the prevention of data silos
Thirdly, using big data for research and development moves businesses from historical to predictive decision-making. This allows them to stay ahead of the market. Moreover, it encourages R&D departments to develop solutions relevant to the near future instead of the rapidly-passing present.
In other words, using the right data prevents brands from spending their money and energy on products and services that are predestined to fail. But what are the real-life applications of data in research and development? And are there any exciting ways that companies are already using it? Let’s find out.
Apple, Beddit, & UCLA
One of the best examples of a company expertly using data to develop new products comes from Apple.
Back in 2017, the company acquired Beddit. This newly acquired business specialized in manufacturing sleep tracking equipment and using the information to gamify sleep improvement. Three years later, Apple released its own version of a sleep-tracking app, made especially for the wearable Apple Watch.
Quite similarly, UCLA announced that it was launching a three-year study that would focus on mental health. By gathering sleep, physical activity, heart rate, and lifestyle data from the Apple Watch, this study aims to find a connection between these health factors and the symptoms of depression and anxiety.
This announcement makes it clear how access to high-quality, well-processed data helps companies make the right R&D choices. Especially as one of the newest features of Watch OS8 is going to be an app dedicated to mindfulness and mental health.
Tesla’s Firmware Updates
Another super-interesting way data helps companies make better products comes from Tesla.
Because these smart cars are equipped with multiple sensors that track user behavior and car performance (regardless of whether the autopilot function is enabled or not), the company successfully diagnosed an overheating issue in 2014. Then, it resolved the problem with a firmware update, automatically installed on all cars, to stop it from recurring.
The Exciting Possibilities of Using Data in Tech R&D
Big companies like Tesla or Apple are not the only ones who can utilize data to develop relevant products. Thanks to the wide availability of data sources, almost any player in the tech industry can do the same.
Software solutions like eye-tracking add-ons can help web designers develop UX features fully optimized for emerging consumer behaviors. Similarly, product developers can keep an eye out for relevant automation shortcuts on service websites like IFTTT.
By tracking how community members use its products and seeing what custom solutions they create, these manufacturers can produce relevant software updates. Furthermore, they can gather and use the data to develop even better products with features their current line-up doesn’t provide.
Applying knowledge derived from big data to tech research and development is, undoubtedly, the key to staying relevant (and solvent) in today’s highly competitive tech market.
However, to get the absolute most out of the available information, organizations must understand the importance of consistent collection methods, expert interpretation, and the concept of the margin of error. Only then can they look for ways to integrate big data into their R&D processes.
About the Author
Natasha Lane is a lady of a keyboard with a rich history of working in the IT and digital marketing fields. She is always happy to collaborate with awesome blogs and share her knowledge all around the web. Besides content creating, Natasha is nowadays quite passionate about helping small business to grow strong.
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