In this guest post, Ciaran Dynes, chief product officer at data integration platform, Matillion, explores the role of cloud data in informing decisions that reduce global impact
As the world turns its attention to sustainability, businesses recognise they need to innovate to fight climate change. Many are starting by considering their energy footprint, and turning to renewable sources to preserve natural, finite alternatives and stave off the effects of rising temperatures.
The use of data, however, deserves far more attention. People often compare data to oil, but data is different in one important area and that’s re-use. It can be consistently taken, reused and applied to understand human behaviour and its environmental impact, if we’re able to deploy it in the right way.
But navigating the variety and velocity of data that businesses produce is not easy. Across all sectors, there are countless examples of organisations struggling to make sense of information because it is sprawled out across different departments. Something as seemingly simple as electricity consumption data, for example, becomes difficult to use if data teams cannot easily aggregate and draw insights from it.
It’s a challenge that is prompting many to turn to the cloud, only to realise that solely migrating to the cloud doesn’t make their organisation automatically more productive. Once they’ve moved to the cloud, the way these businesses run analytics inevitably must change. Faced with a wave of more complex and dynamic data – aggregated from different factories, fields and energy sources – data teams need to work faster to manage the refined data.
Modern cloud data approaches offer the opportunity to streamline this process and develop meaningful outcomes that make a positive, sustainable difference, yet remain unexplored by many.
Where data and analytics is making a difference
There are countless businesses – and industries – that have the opportunity to do more to advance green initiatives, both through improved business intelligence and advanced analytics. It’s by no means a far-fetched scenario, and in fact, a lot more feasible than you might think.
Take the insurance industry, for example. Insurers need accurate environmental insights to gain a more holistic view of the factors influencing their underwriting, and ensure complete coverage in the policies they issue. Yet right now we’re experiencing highly unpredictable weather patterns, with sea levels rising, flooding events becoming more common and wildfires breaking out in parts of the world – even in this country – where they never have before.
Tracking the effects of climate change and the repercussions for the insurance industry is imperative. It’s undoubtedly a herculean task, but one that can be made manageable with the power of data. If used correctly, data analytics promises to consistently predict localised climate emergencies.
Using those insights helps brokers to communicate expectations to – and inform the policies that impact – vulnerable populations who are facing uncertainty over the protection of their properties. All of which means more accurate coverage, while managing the effects of climate change and discouraging initiatives with potentially negative environmental repercussions.
The potential applications of data go beyond finance, too. In the quest for zero-waste agriculture, the consolidation and analysis of data is already critical to feeding the world through natural, sustainable solutions. Rapid access to constantly changing data, such as weather patterns, is helping firms in the biotech sector predict trends in wastage, optimise supply chains and make decisions that sustain a circular agricultural value chain. Like many other industries, it is in the process of scaling, and that means a lack of visibility into and control over data silos simply isn’t an option. The consolidation and aggregation of data is pivotal to their future success.
The travel industry has been using weather predictions to schedule advertising to its customers for years. If it is going to rain in London this week, why not promote a holiday in Greece to lift the gloom of your rain soaked weekend BBQ?
There are countless more applications of data that we can explore to improve society around us, but right now we’re just scratching the surface of the best ways to do so.
The obstacles to data-driven sustainability
Despite the digital transformation we’ve witnessed in conventional industries, many firms struggle to drive positive environmental outcomes from their data as a result of misconceptions around their approach.
More broadly, some companies trying to remain resilient during economic turbulence may prioritise corporate goals over using data to meet sustainability targets. Government policy inevitably plays an important role here, and closer alignment with climate science is needed to influence corporate objectives and ensure data frameworks and regulations help support environmental use cases for data.
At a more granular level, stakeholders across an organisation need the intelligence to make the right decisions, at the right time, to support their environmental goals. As external factors such as regulation and consumer demands evolve, data teams need to consistently refine, refresh and realign their sources of data so they’re able to act both reactively and preventatively and best align with those objectives.
Remember the insurance example we mentioned earlier? The challenge doesn’t lie in the data itself. It’s in how it’s distributed and stored; masses of information surrounding policies, policyholders, risk assessments and claims histories are dispersed across multiple platforms and in different formats, ranging from ERP platforms to more specialist claims management software. That data becomes difficult to locate, and even more difficult to extract value from. So how can sustainability businesses become more productive with the data they have?
The value of a democratised cloud data platform
With the marrying of big data, a cloud-based platform and the right business model, businesses seeking to enhance their green credentials can keep up with the external changes around them. A modern cloud-based approach of “extract, load, transform and sync” is a crucial piece of the puzzle, allowing teams to consolidate enriched data sources and make it accessible for all from centralised platforms.
We are now in an era where these cloud platforms are not only solving the analytics requirements of the business but also acting as a data operating system from which data can be synchronised back to the applications that customers are interacting with in real time thereby enhancing and tailoring the experience to that user. Automating the influx of unstructured data, means data teams can become more productive, by spending significantly more time on solving business issues at the core of their sustainability mission, and less on data gathering. Like energy, data must be treated like a continuously recirculating resource – it just needs the right unified strategy to achieve outcomes for the greater good.