Friends, about two months ago, we touched upon on The New Normal
- Making Treasury function more efficient
- Bank Account management
- Cash flow forecasting
- Cash pooling obstacles
Readers found it interesting, and asked for more information.
Big data: What’s the big deal?
- Understanding what big data means is more important than defining it.
- The availability of big data is not an immediate way to improve your business – what matters is using existing data to create actionable intelligence.
- For intelligence to have value it must deliver answers in time to make a difference to business outcomes.
- Data visualisation tools offer ways to processing and drawing intelligence from unstructured data
With so much buzz around the term “Big Data”, you might think that its value is proportional to its quantity: the more data you have, the better. Get out there and start collecting as much as you can!
Undoubtedly big data is opening doors to new ways of understanding the world around us and to predicting behaviour. It is changing the way we do business, the way we are governed, the way we look after ourselves and even the way we learn.
But big data’s worth lies not in its “big-ness” , nor in amassing ever greater quantities of it; but rather in the questions you use it to answer – answers that will make your business better.
Instead of collecting data simply for the sake of it, big data’s real value comes from being smarter in the way you use the data you probably already have.
So just what is big data, and what’s the big deal?
We are living in a world producing a constant deluge of data. According to IBM, more than 90 per cent of all the data in existence was created in just the last two years. It estimates that each day another quintillion bytes of data are generated – that’s about a billion gigabytes every 24 hours, or the equivalent of a very large pile of hard drives!
This data takes many forms. Every button pressed, every purchase made, every sensor activated – it all produces data. And data is more than simply numeric. Data can also be extracted from comments posted on social media, from tweets, even from photo sharing, translating consumer sentiment into quantifiable, measurable, usable information.
On its own, each isolated piece of data has little value. But mapped together with other data, what was apparently worthless becomes an invaluable insight into human behavior, mapping out your business environment and that of your competitors.
In business terms, understanding what big data means is more important than defining what it is. Big data, is not a disruptive technology, nor is its availability an immediate way to improve your business performance.
In fact, as the image below illustrates, big data is nothing particularly new. History has many examples of how technological progress has driven the generation of quantities of data well ahead of that which we feel able to manage or consume.
Big data happens in every part of history – we always create more than we can consume!
Today the benefits from the massive quantities of data we generate are only realised when it is processed using a growing array of visualisation tools. By moving beyond a simple spreadsheet, software such as QlikView, SAP Visual Intelligence and other tools allow us a dynamic visualisation of big data, bringing out the myriad of links and interconnections behind the information.
This is the critical step in transforming the unstructured mass of big data into what we call “Actionable Intelligence“.
Taking a complex, real time, constantly evolving picture of a business and translating it into easily understood visuals, these tools enable us to drill into the many levels of data, understand the connections between them and open up new understanding and opportunities. This process of “business discovery” enables businesses to see a new, more complete and more encompassing business model.
And, as technology develops and more data is created, the potential for generating actionable intelligence across more and more areas is set to grow.
Retailers, for example, can gather data from customer loyalty cards and link them to other data from their customers’ social networks. Such intelligence will allow them to better understand who their customers are and their influence upon other existing or potential customers. This can be actioned through better targeting of their marketing, making it more efficient and ultimately more effective, and allowing better predictions of purchasing behaviour.
Let’s take another hypothetical example of actionable intelligence: A man is walking down the street in Singapore and he faints because his pacemaker has stopped. An ambulance is then called to the scene. A few minutes earlier a woman had tweeted seeing a man that appeared dazed. Fifteen minutes earlier security cameras had captured this man looking confused because the pacemaker was failing, and for the past few hours the pacemaker status had indicated failure. But if we had correlated the data, the ambulance doctors could already have taken preventive measures and improved the outcome for the man.
The scenario above might sound far-fetched, but think about how what we take for granted today sounded equally far-fetched just a few years ago:
- Investors keeping track of thousands of stocks at once without the aid of a massive computer system, something we can now do on the move in the palm of our hand.
- Manufacturing companies able to view the real time performance of every manufacturing line in every plant in every location around the world by computer. Today, this is expected in any enterprise resource planning (ERP) system. What we considered “Big Data” 30 years ago is not complex and challenging now. Looking three decades into the future, today’s Big Data will also be simple.
The key is the combination of tools, people and processes – the “capability set” which allows us to capture and process this data in order to deliver actionable intelligence in time to improve business outcomes.
Speed is of the essence: intelligence, after all, is only of real value if you receive it quickly enough to make use of it.
Already next generation leaders are leveraging big data and developing capabilities delivering greater levels of actionable intelligence. By pulling in data from complex, high volume sources like social media sentiment, customer movements tracked via cellphone apps, and real time resource location they can determine instantly what the optimum future outcome can be, improving the accuracy of business planning and overall corporate performance.
These capabilities enable companies to seize opportunities that others can’t. Meanwhile companies which fail to leverage their own big data to extract actionable intelligence are open to missing out on potentially massive savings, and vulnerable to succumbing to their competitors and current marketplace forces.
To take one recent example, industrial giant GE says it believes the utility industry can extract around $150 billion of unrealised efficiencies by using already existing data in smarter ways.
Using what it calls “immersive” data visualisation, GE’s Grid IQ software allows utility firms to better monitor their infrastructure, applying data streams to deliver intelligence that enables them to respond to business changes at high speed and, critically, in time to make a difference.
The message then to any business is clear: smart use of data to answer key questions about your business is essential to building a more encompassing business model and giving you the edge on your competitors.
While businesses who have yet to start developing actionable intelligence capabilities are at risk of becoming obsolete.
[source: Keith Carter – Think Business, a publication of NUS Business School in Singapore]
Keith Carter is an adjunct associate professor in the Department of Decision Sciences at NUS Business School, Singapore
Suresh Shah, M.D., Pathfinders Enterprise