“Answers to some of society’s most pressing challenges across medicine, climate change, space and more are buried in massive amounts of data, and the convergence of 5G, artificial intelligence (AI), the internet of things (IoT), high-performance computing and other emerging technologies is helping to unlock them.” – Antonio Neri
The potential of data to transform sectors as diverse as life sciences, banking, manufacturing, retail, government and healthcare is becoming more apparent by the day. This has never been more apparent than now with the presence of COVID-19.
Seen in that light, it’s clear that businesses of all sizes need to embrace big data, not just at an operational level, but for the paradigm shift it is, a resource that enables and empowers everything we do.
Unlocking the value of big data for your organisation, lies in understanding how you can use it to tackle challenges and open up opportunities unique to your sector – in a way that adds value both for your organisation and your customers.
- Let’s start with the definitions
- What are the risks and opportunities
- How is big data changing
- The characteristics and evolution of big data
- How can businesses benefit from big data
- How are businesses using big data
- Why businesses can’t afford not to embrace big data
- The future of big data for business
Let’s start with the definitions
What is big data?
According to Gartner, the definition of big data is “High volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.”
In other words, what do we do with the deluge of data flooding in from all the devices, apps and gadgets we use? From smart home devices and wearable tech at an individual level, to smart solutions used by businesses and organisations. How do we extract value and make the most of this unique, contemporary resource?
What is the Internet of Things?
Collectively, smart gadgets are known as the Internet of Things (IoT), described by Business Insider as “the rapidly growing network of connected objects that are able to collect and exchange data using embedded sensors.” By 2026, they forecast that there will be more than 64 billion IoT devices installed around the world, with the World Economic Forum estimating that 463 exabytes of data will be created each day by 2025.
What are the risks and opportunities
We’re all leaving a growing trail of data that reveals our likes, habits, preferences and behaviours – a potential goldmine of information and opportunity for savvy businesses.
The opportunity presented by the IoT is certainly appealing. An always-on, smart future where everything we do and every place we go is combined to help us. The organisations playing an active role in making that happen will continue to stand out from the crowd but alongside the opportunities there are also risks and challenges – including privacy, transparency and data security.
GDPR has made ‘data protection by design and default’ a legal requirement, with businesses having to integrate data protection into everything they do. Cautious, careful and considerate use of data can help leverage the value and insight buried within it. The result is a uniformed and synchronised platform that enables better outcomes for the customer, and the business.
How is big data changing
Just a few years ago, the biggest headache for business was the sheer size of big data. It came in huge volumes, it wasn’t in one convenient location, and lots of it was unstructured free text and images.
But with big data technologies like artificial intelligence (AI) and machine learning making it much easier to manage, analyse and understand big data, it’s becoming much more usable – including pictures, video and voice data. And because machine learning models are designed to learn from data rather than programming, the more data they use, the better they get.
Now, many businesses want as much data as they can get. Increasingly, the challenge for organisations is understanding and unlocking the real value of big data – for their customers and their organisation.
The characteristics and evolution of big data
As Gartner’s definition suggests, big data was originally described in terms of volume, variety and velocity, with IBM adding veracity and coining the term ‘the four Vs’ in 2012.
The vast amount of data generated every second, by organisations and consumers, with many data sets too large to store or analyse using traditional database technologies.
Data comes in numerous shapes and forms, including geospatial data, website logs, tweets, photos and videos.
The speed of data creation and use is increasing, which means processing, storage and analysis must accelerate in tandem, before data becomes obsolete. Business advantage lies in having and acting on the most up-to-date information, which means receiving data and insight as soon as possible, then acting with equal speed.
Ensuring the reliability and validity of the insights derived from data is key, with inaccurate data virtually worthless and potentially damaging. The flipside is that chasing veracity can lead to over-cautiousness, as organisations and individuals wait for perfect, clean data before making any decisions.
In the last few years, we’ve also added two further Vs to the list, to reflect the changing nature of big data in the age of big data technologies like AI and machine learning.
Vulnerability – privacy, security and brand reputation
The proliferation of big data has left many people feeling exposed and vulnerable to the way their data is being collected and used. Conversely, a growing number of ever more tech-savvy consumers are willing to sacrifice some privacy as a trade-off to the benefits of digital, personalised technology, but under their own preferences and conditions. Increasingly, people want to be informed about data use and have the ability to easily opt-in or out at any point in time.
Value – solving challenges, meeting needs and exceeding expectations
At the most simplistic level, data has no intrinsic value. It only becomes useful when you’re able to extract the insight needed to solve a particular problem or meet a specific need. Once you can do this, the data acquires value through the business impact and consumer value this insight delivers. Consumers are looking for value in terms of convenience and superior, more relevant content, products and user experiences. Organisations are seeking value via more engaged customers, lower costs and reduced business risk. Value is a two-way model. For both parties to be successful, there has to be a fair exchange – each needs to feel satisfied. This means that big data, and big data analytics, are only valuable if they generate some form of payback.
Thankfully, advances in big data analytics are helping businesses to achieve this more consistently, combating the challenges of data volume, variety, velocity, veracity and vulnerability, while delivering the all-important value. This is being done by:
- Tying insights more closely to business decisions.
- Drawing on, integrating and analysing new data sources.
- Moving beyond simpler business intelligence and analysis, towards diagnostic, predictive and prescriptive big data analytics.
- Developing data strategies that relate closely to clearly defined business goals, outcomes and use cases, rather than simply deciding a ‘big data strategy’ is required and proceeding in a business vacuum.
To harness the full value that big data can offer, organisations, governments and regulators will need to continue investing time and money in educating both the general public and businesses about how to manage the vulnerabilities and value opportunities that big data presents.
How can businesses benefit from big data?
While the 6 Vs describe the challenges associated with big data, they also reflect the opportunities, including targeted big data marketing built on a single customer view, smart interaction and personalisation; together with the chance to build a more trusted, valued brand.
- A greater volume of data means a greater volume and depth of insight into customer behaviour, if harnessed effectively.
- Data variety and the ability to harness data in all its different forms, together, gives businesses a more holistic view and unified insights.
- Real-time analysis helps businesses deal with velocity, enabling you to make decisions based on the most up-to-date information.
- Veracity often depends on individual users, meaning engagement with data and a commitment to cleaning it up, and keeping it clean, are critical on a person by person basis.
- GDPR’s ‘data protection by design and default’ – legally requiring organisations to integrate data protection into everything they do – is helping to provide reassurance and address customers’ concerns, as data usage and value become more transparent.
- Big data analytics have an increasingly important role to play in data security and are already transforming intrusion detection, differential privacy, digital watermarking and malware countermeasures.
- Security is also about building brand reputation and trust. Strong security practices, including the use of advanced analytics capabilities to manage privacy and security challenges, can set businesses apart from the competition and create comfort and confidence with the public.
How are businesses using big data?
Organisations use big data for a range of reasons, from enhancing customer experience and targeting marketing more effectively, to reducing costs, improving processes and enhancing security.
For example, entertainment companies analyse customer and behavioural data to create detailed customer profiles for personalising content and measuring content performance. In finance, big data plays a huge role in analysing risk, from preventing fraud to supporting decision making.
1. Big data in healthcare – working alongside humans
Big data has significant socio-economic benefits. For example, Harvard Medical School compared the accuracy of machine learning systems against human pathologists in detecting breast cancer. Machine learning was 92% accurate, humans were 96% accurate, but together, they were 99.5% accurate. That translates to 56,000 fewer misread breast scans in the US every year.
2. Big data in finance – making credit more inclusive
In the UK, around 5.4 million people are credit invisible, excluded from large parts of the credit market, either because they have limited credit history, or no credit file at all.
On top of that, an estimated 2.5 million people have been marginally declined, meaning that, despite having a full credit history, they’ve been narrowly rejected for credit through automated decision management based on scoring policies set against segments, rather than people. While only a small percentage of that group would likely default on their payments, lenders typically set a cut-off rate that excludes many potentially good borrowers.
In total, that’s around 7.9 million people who suffer from financial exclusion. For many, it’s a catch-22 situation. If you’ve never had credit, it’s harder to get credit. With limited options, many turn to sub-prime lending – at the cost of unfavourable interest rates. And the vicious circle is complete.
As an industry, we’re doing more to address the issue and make the invisible, visible. Firstly, because improving financial inclusion will benefit society, secondly because this group represents a huge untapped market.
To offer better credit options, you need to reduce risk. To do that, you need to know enough about everyone to feel confident they can make payments without getting into difficulty. In short, perform more detailed affordability assessments.
Beneficial new data
New data such as the bank account data now available through open banking APIs provides a detailed look at a person’s income and expenditure – the day-to-day reality of their financial situation. Pair this kind of new data with advanced analytics to unlock the insight it provides, and you get a much more robust view of a person’s affordability.
Providing the consent is there, which requires transparency and work to ensure customers are aware of the potential benefits, we believe open banking, alongside other non-traditional data sources like rental data, will be transformative for thin-file and marginally declined applicants. Our research shows that people will share their data if the value is evident, and in this case, the value is easier access to finance.
Using big data to enhance your credit decisions
New data alongside new analytical techniques and advanced technological power, offers significant benefits to all, especially consumers. To make the most of the opportunity:
- Use the best data – in terms of both data assets and data quality.
- Partner with a provider who aligns to your brand promise and advocates the best and most effective methodology.
- Use the right decisioning capability to automate the process, enabling real-time, fair, accurate and efficient decisions to be made, and acted on, in the moments that matter.
Why businesses can’t afford not to embrace big data
As Forbes Technology Council member, Vlad Flaks, puts it, AI technologies are blooming and bearing fruit everywhere, personalisation and smart interaction are becoming standard features of customer experience and customer data security and data policies matter more than ever.
“Being data-driven doesn’t mean adopting the latest AI tools into your tech stack immediately, but it does mean making decisions mindfully, considering all your data. Data isn’t just something that sits in silos to help you make decisions; it’s a treasure you have to protect.”
Flaks argues that companies who don’t become data-driven will risk going under, potentially damage their brand by not creating relevant, personalised user experiences and waste money on marketing, with the quality of marketing insights and decisions depending on the quality of your data analytics.
Can businesses of all sizes benefit from big data?
The answer is yes. Just because it’s called big data, doesn’t mean its use is limited to big corporations. Businesses of any size can use big data and advanced analytics tools to better understand their customers, tap into new markets and cut out unnecessary costs, all with evidence to support their decisions.
The questions small and medium sized businesses (SMEs) need to answer are what data do they own? What data can they access from others? How will they create, collate and analyse these data sets and how will it generate value and revenue for their business? More than likely, they’ll need to incorporate external data and systems with their own to uncover new insights.
Using big data can add value in all kinds of ways, from automating routine tasks and saving time and money, to unlocking valuable customer insights for big data marketing from social networks and sources such as geolocation data.
There are many ways SMEs can make use of data. It could be buying targeted marketing data sets, hiring a digital agency to help with re-marketing or it could be as simple as feeding customer information into a CRM system to better understand target audiences.
The future of big data for business
For businesses, data is fuelling a transformation in customer experience, with organisations increasingly able to interact with individuals and tailor products and services around their needs and preferences. And that’s not all. As Gartner suggests in their strategic technology trends for 2020, data is also supercharging the way organisations work.
From hyperautomation enabling businesses to automate processes, enhance human capabilities and explore how to grow and innovate by creating their own digital twin. To artificial intelligence driving the democratisation of data, making it more accessible and understandable to a broader range of people.
Asking yourself how you can deliver on the promise of big data to add value to your organisation, customers and the wider world is a key place to start if you want to develop a truly effective strategy.
Unlocking the true value of big data
Whilst technology has brought us to this point and will continue to drive us forward, it’s up to people to define the true and lasting value of this incredible global resource. Not only by optimising how it’s generated, stored, managed, processed and protected, but by defining the ‘value’ we extract from it – in social as well as economic terms.
Just like any other resource, the debate around who benefits from data and who shoulders the risks will ultimately inform how it will evolve and shape our collective future.