Is underutilizing your data hurting your bottom line?

In today’s digital world, everyone is generating data. With digital information being created, analyzed, and stored at an incredible rate, data generation has become a global phenomenon.  

According to Forbes, 90% of the world’s data was generated between 2016 and 2018. But according to similar studies, only less than 2% of that data was being actively used. 

With the amount of data exploding and continuous advancements in technology, companies can’t compete in the market without actively using data. 

Companies know they have data. The real questions they’re asking are, “How do we use it? How do we find value in it? How can we build our ROI with it?” 

By looking at data through two high-level lenses – automation and knowledge gaining -companies can benefit by using data and AI to improve various parts of their business. This can include predicting failures, optimizing operations, and making better business decisions. Data can help companies gain greater insights, increase productivity, and accelerate innovation cycles, ultimately transforming their products and services for the better. 


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Data is empowering both humans and machines to do what they do best—AI excels in handling large-scale data processing and pattern recognition, freeing up humans to focus on more creative or strategic tasks. As a result, companies are better equipped to innovate and develop superior products, which can increase their overall value and success. 

The challenge today is that many businesses are solely product focused with their data. Companies have connected products and IoT systems in places that are collecting substantial amounts of data, but they’ve failed to connect their data strategy to a robust and obvious value proposition—they don’t view their data as an asset, like the product. Their business objective starts and ends with delivering a device, leaving them with data they don’t know how to use. They’ve hit a roadblock in their data journey, and they’re left facing the pressure of building a strong return on investment (ROI). 

“We see companies spending money collecting data, whether it be through a connected product or other means, but they’re not able to take that data, look at the learnings or the trends, and use that information to increase business revenue,” says Steve Honderd, Twisthink Chief Financial Officer. 

One of the tools we use to help companies get past this barrier and identify where they are with their data is through the data pyramid.

The data pyramid, also known as the data science hierarchy of needs, provides a contextual structure to articulate the steps to improve value with data. As companies move up the pyramid, their potential for business growth and success increases exponentially. With each step up, you have increased value, a higher level of intelligence, and a greater return on your investment. 

Many companies are finding themselves stuck at the bottom of the pyramid, struggling to move beyond the descriptive level, hindering their ability to create new value. The challenge lies in getting beyond using data for their products and IoT systems and engineering it to transform their business both internally and externally. 

“We’ve seen companies be successful when they take their data, make it valuable to the end user, to their customers, and then set up recurring revenue streams through a subscription or other ways to keep providing the data,” says Steve. 

For example, if a company wants to use data to track assets in real time and understand the state of their battery level, they would be able to see their batteries failing at the descriptive level. At the diagnostic level, they could see trends on why batteries fail and when batteries need to be replaced. At the predictive level, they could predict how long their battery will last for the future. And then at the prescriptive level, they could optimize how their machine runs to extend battery life.  

By using the data pyramid as a guide, companies can identify their current position and take steps towards reaching their desired outcome. By leveraging historical and real-time trends, businesses can uncover new opportunities to innovate beyond their current offerings. With greater insights and a higher level of automation, businesses can imagine and experiment in new domains. 

Are you ready to move from data collection to outcome generation? Explore the full potential of your data with Twisthink’s Data Value Assessment where we identify new data opportunities and use cases that create immediate business impact. Connect with us to learn more. 


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Turn your data into immediate business value?

Our data assessment will help you better understand your data, identify feasible and viable data opportunities, and provide strategic recommendations on how you can add a whole new level of intelligence to your business model.

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Big data technology and data science. Data scientist querying, analysing and visualizing complex data set on virtual screen. Data flow concept. Business analytics, finance, neural network, AI, ML.

As our Director of Data Science, Ryan is responsible for bringing value to our team and clients by designing sensor solutions and data analytics pipelines that create trustworthy decisions and insights . He leads a team of talented system thinkers who approach challenges through the lenses of sensors, data, AI, and algorithms.


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