With the advent of the internet, wearable communication devices, and the use of artificial intelligence in our everyday lives, we are seeing some formidable technological advances, possibly the greatest since the beginning of time, but what big advances are so big with the right strategies it can quickly become useless and as an entrepreneur it can also become a costly mistake.
This is why the use of data for research and development is so critical; On the one hand, it is an excellent opportunity to follow the relevant trends and requirements of the market in the future; second, it is an alternative entry point and support for speculative design. Therefore, the use of data can be the key to identify and solve the great challenges facing humanity in the years to come. We’re talking about everything from water scarcity, climate change, the need to develop safe and autonomous cars, etc.
The Benefits of Using Data for Research & Development
From a purely business perspective, using big data in R&D has several important advantages. On the one hand, it is an effective way to save time and money, especially if you use existing information or invest in continuous data collection and analysis. It is a more accurate way of collecting, interpreting, and applying information. Well-designed recording systems give companies access to more relevant data. McKinsey, for example, emphasizes the potential of big data in the health and pharmaceutical industries. It states that big data allows for:
- more streamlined clinical trial enrollment
- real-time data collection (and reaction, when necessary)
- the prevention of data silos
Third, the use of big data for research and development moves companies from historical to forward-looking decisions, keeping them one step ahead of the market and encouraging R&D departments to develop solutions that are relevant to the near future rather than the fast-moving present. In other words, using the right data prevents brands from wasting their money and energy on doomed products and services. But what are the real uses of data in research and development? find out.
Apple, Beddit, & UCLA
One of the best examples of a company that uses data skillfully to create new products comes from Apple: In 2017, it acquired Beddit, a newly acquired company that specializes in the manufacture of sleep tracking devices and the use of sleep specializes in improving sleep. Apple has released its own version of a sleep tracking app specifically designed for the wearable Apple Watch. Similarly, UCLA announced it would start a three-year study that would focus on mental health. With Apple Watch data, this study aims to find a link between these health determinants and symptoms of depression and anxiety. This announcement highlights how having access to quality, well-processed data helps businesses make the right R&D decisions. The newest features of Watch OS8 will be an app dedicated to mindfulness and mental health.
Tesla’s Firmware Updates
Another super cool way data is helping companies make better products is coming from Tesla. Because these smart cars are equipped with multiple sensors that track user behavior and vehicle performance (whether or not the autopilot is enabled), the company successfully diagnosed an overheating problem in 2014. Then it automatically solved the problem with a firmware update installed on all cars to prevent recurrence.
The Exciting Possibilities of Using Data in Tech R&D
Not only large companies like Tesla or Apple can develop relevant products from data. Thanks to the wide availability of data sources, almost any player in the technology industry can do the same. Software solutions like eye tracking plugins can help web designers. Develop fully optimized UX capabilities for emerging consumer behavior. Likewise, product developers can look out for relevant automation shortcuts on service websites such as IFTTT. By tracking how community members use their products and seeing what custom solutions they create, these manufacturers can create relevant products. In addition, they can collect and use the data to develop even better products with features that their current product line does not offer.
In Closing
Applying the knowledge gained from big data to research and technological development is undoubtedly the key to staying relevant (and solvent) in today’s highly competitive technology market. However, to get the most out of the information available, organizations need to understand the importance of consistent survey methods, expert interpretation, and the concept of margin of error. Only then can they look for ways to integrate big data into their R&D processes.
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