Today we are witnessing a growing challenge that intersects technology and sustainability: the true cost of big data. While data is often termed the ‘new oil’, it is important to recognise not just its value but its environmental and operational costs.
Firstly, we’re witnessing an exponential growth in data collection, with $215 billion spent in 2021 alone on big data and business analytics solutions, according to IDC.
The importance of analysing the right data
IDC also forecasts that the amount of data ‘created, captured, copied and consumed in the world’ will continue to climb at a rapid pace, estimating that the amount of data created over the next three years will be more than all the data created over the past 30 years.
This trend is not slowing down, with researchers expecting a growth of 31% in the data science sector by 2030. But we should ask ourselves – at what cost?
We’re grappling with inefficiencies and complexities from accumulating non-essential data. This not only bloats our systems but also our environmental footprint, significantly impacting our carbon emissions due to the extensive energy requirements of large data centres.
“You really want to make sure you are analysing the right data for the right reasons and in the right location within the right cost structure,” says Rich Karpinski, senior research analyst, 451 Research, part of S&P Global Market Intelligence.
“Specifically organisations need a strategy for determining which data is most important and an IT approach to help manage it all.”
Furthermore, as our industries evolve with technology and AI, we face a stark reality. Many businesses remain unprepared for the long-term implications of IoT, lacking the necessary interconnected systems for a seamless Industry 4.0 transition.
According to the KPMG 2021 Fourth Industrial Revolution Benchmark Report 2 out of 3 organisations are not well-prepared to deal with changes resulting from the Fourth Industrial Revolution, up from 54% the previous year.
Decision-makers must strategise not just for the immediate future, but for a sustainable and efficient one, addressing the direct impacts on our costs, security, and most importantly, our planet.
Garbage in, garbage out
According to research by Veritas Technologies, 77% of the data that organisations capture is either redundant, obsolete or trivial, or altogether unclassified.
Poor data quality can have a significant impact on your business. According to Gartner, ‘organisations believe poor data quality to be responsible for an average of $15 million per year in losses,’ and nearly 60% of those surveyed didn’t know how much bad data costs their businesses because they don’t measure it in the first place.
Poor quality data understandably leads to data distrust, According to Vanson Bourne, 77% of surveyed IT decision makers don’t completely trust the data in their organisation and there are further productivity impacts with data needing to be reworked and an average of 4 hours lost per employee per working week to resolve data analysis related issues.
Essential data
Knowing what data you need is at the core of the concept of essential data. And to identify your organisation’s essential data, you need to be clear on what objectives you are trying to achieve or what challenge or problem you are trying to address by collecting or harvesting data.
For example, if you are a third party logistics provider and you are implementing a technology solution to track your parcel cages, be clear about why you’re tracking the cages and then decide what data points you need for that purpose. It may be just location data to keep track of their location and to stocktake. But if you are having an issue with theft, you may also want to collect data on device tampering.
Rich Karpinski, senior research analyst, 451 Research, part of S&P Global Market Intelligence, makes an important point in terms of being able to successfully implement a technology solution. He says “while the desire to leverage IoT data to help transform an organisation is valuable, there is often a tipping point where projects move to production scale and things get real and then get challenging” due to the massive number of endpoints and the amount of data generated by IoT deployments.
This is where the idea of essential data can help in still getting the value out of the data without the implementation headaches.
You can’t manage what you can’t measure
The business impact of lack of data, poor data quality or poor data management depends on the role data plays in the organisation’s processes. The following is a list of risks or impacts that is common across many organisations.
- Lost revenue
- Missed opportunities in terms of leads, sales and cost savings
- Inefficient operations
- Low customer satisfaction
- Lack of compliance
- Increased costs
How IoT helps
Once you know what data you want to collect and analyse, you need to ensure that the technology solution you select can collect the right data at the right point in time, and translate that data into actionable insights.
Internet of Things (IoT) solutions come in many flavours, and there is one to suit almost every use case.
At Thinxtra we work through your unique use case and align the most appropriate end-to-end solution to meet your business requirements, ensuring we collect the right data at the right time, minimising unnecessary data collecting and maximising your insights.
Our expertise and leadership in IoT means we’ve had extensive field experience and know what works, when and how, minimising any surprises when it comes time to implement and deliver.
