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2 Compelling Reasons Why Innovative Organisations are including Big Data Capabilities in their 5-Year Strategic Plans
FEB 21, 2017 05:03 AM
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Blog post By Hoani Barker.


 

In today’s increasingly interconnected world of trade and commerce, big data continues to prove its game-changer status. Innovative organisations understand this and are actively incorporating big data strategies into building their futures.

If you’re a business owner, strategic consultant, or key decision maker in your organisation, here are two great reasons why you should include big data capabilities in your 5-year strategic plan:

1)     Customer Insights: gain access to invaluable intelligence and insight into what your customers want now and into the future, and

2)     Optimise Operational Efficiency: empower your business to operate more lean and efficiently; saving you precious time and capital which can be put to better use.

Before we address the above two points, let’s start by asking the obvious question: what is big data? A simple way to define it is:

A term for data sets so large and complex that traditional data processing applications are inadequate.

More simply: data that is inconveniently large.

So how large is too large you might ask?

According to Forbes magazine, in 2011 we humans had created 1.8 zettabytes of information. That's 1.8 trillion gigabytes of data, which is enough information to fill 57.5 billion 32GB Apple iPads.

That’s enough iPads to build a great iPad wall of China twice as tall as the original.

It's now estimated that by 2020 that number will rise to around 44 zettabytes. That’s 1.7 megabytes of new information created every second, for every human being on the planet.

Most of this data creation is linked to the proliferation of The Internet of Things (IoT), which is any device capable of collecting and transmitting data via the internet. Think things like smart phones, iPads, fit bits, other smart wearable devices, smart home appliances, smart homes, micro sensors, laptops, internet enabled raspberry pi devices etc. etc.

With that in mind, in the next 2 years we will almost double the amount of ‘smart’ devices on earth to 40 billion. Over 5 times the world’s current population.

Now although the sheer magnitude of data creation we humans are creating is kind of (really) hard to deal with, big data per se can also be considered the acceleration of data creation, complexity of data formulation, and the expanding relational values between the many different types of data being created. All of which are making the processing of ‘big’ data, and our subsequent understanding of its value, increasingly challenging.

Without being able to understand these complexities and relationships more deeply, the majority of big data will remain nothing more than digital hieroglyphs without a key.

So that’s Big Data. Massive, hey? But what does that mean for you and me?

Imagine this…

You’re planning a holiday to Switzerland and you start researching popular places to visit on Google. You then begin to realise you have no time for a holiday, so you put the idea on hold. The very next day you open your web browser, type in a search query, then get bombarded with amazing flight deals to Switzerland popping up on every website you visit; keeping the dream alive.

Sound familiar?

Companies like Google, Apple and Facebook who dominate the netisphere are leaders in what’s known as dynamic advertising. Dynamic ads contain algorithms that track the environment, browsing history and other net usage norms of end-users, then custom build personalised billboards in real-time.

In this example big data analytics is the analysis of information the end-user surrenders every time they install, update, search or sign up to a new social media site, web application, online subscription, gaming forum, web browser, e-commerce site, and so on. At an incredible scale.

Innovative companies have realised the benefits of leveraging this data, and will include the acquisition of such information in their terms of use.

So whenever someone clicks that ‘accept the terms and conditions’ button, or hands over their email address, they’re generally saying: yes, you can track my usage, store my data, and send me updates. 

The way this data is stored is usually structured and relatively easy to analyse.

For example: which website a person visits before or after hitting the site in question; how long they stay on a particular webpage within the site before moving on; what products they generally browse, purchase, rate, or add-to-cart; how long it takes before they close a pop-up window; how many pop-up windows they actually click on, and the list goes on and on.

And voilà. Cheap flights, Swiss ski deals and ski equipment ads for days.

Big data is also, however, the analysis of structured, semi and unstructured (static and dynamic) information which is generated, captured and stored through IoTs, private intranets, public and private databases, cloud platforms, virtual machines, physical hard drives, geographic information systems and data warehouses.

This includes analysing data sets not recorded in a conventional manner, such as in tables, lists or files.

This type of information is known as unstructured data. Information that does not have a pre-defined data model or is not organised in a predefined manner.

Data that is generally text heavy; like tweets and Facebook posts, and contain things like dates, numbers and facts. Information that is harder to sort and sift for gold.

Unstructured data is by its very nature harder to track and analyse adequately, but this is an area demanding a lot of attention.

Many experts at the cutting edge of the field, such as data and computer scientists and engineers, statisticians, mathematicians, and even physicians view big data as a potential holy grail; containing insights into the human condition, and answers to how we can optimise human development.

By better understanding the behavioural habits and needs of individuals in all aspects of day-to-day life, whether it be in health, travel, politics or economics, we can tailor our future to best suit our needs.

The Tech

When combined with advancements in machine learning and artificial intelligence it’s believed that big data will feed the development of such technologies, and compound our ability to learn and expand on the hard and soft sciences at an accelerated rate.

The main challenge here, for small businesses in particular, is obtaining the software solutions and capabilities to gather, monitor, track, store and leverage their data accordingly.

There are several products on the market that innovative organisations are deploying to reap the rewards big data can offer, and in the next 5 years, many of these solutions will become an integral part of standard operational norms.

Products like NoSQL, Oracle, Hadoop, TeraData and Cassandra offer services in management, monitoring, tagging, storage, processing velocity and speed, and analysis of large data sets that will help you transform data into real business benefits.

In my opinion, none of what we have discussed is a bad thing. I’d actually argue the contrary. And in an attempt to highlight why I think this way, I’m going to touch on the benefits big data has for both the consumer and the supplier.

So enough with the information overload (no pun intended) and back to the crux of this article. The reason I recommend your organisation should adopt Big Data capabilities is two-fold.

1)   Customer Insights

In the world of IT consulting, Big Data capability is often packaged into services like cloud computing, business intelligence, advanced analytics, machine learning, CRM and other tech solutions designed to address the impact digital disruption is having on matters of business and management.

By capturing timely insights from the vast amount of customer data mounting in your company database, external third-party sources, social media platforms and the Internet of Things, you can gain a deeper understanding of what your customers want, when they want it, how they want to purchase it, and how much they’re willing to pay for it.

The advent of social media and the rise of the ‘social economy’ has given customers multiple platforms to talk about products they buy (love or hate) with other customers all over the planet. More precisely, in a way that is being observed and captured by data-centric companies. This in turn can have a direct impact on sales and revenue, and the overall direction new product developments take.

Monitoring and analysing data streams offers a real-time look at customer sentiment, which can provide a clear picture from which to develop new strategies and ensure your organisation maintains agility and relevance in the marketplace.

This not only benefits Suppliers. It gives power to the consumers in a way that allows them to have input into the development of products they purchase. It also gives them greater opportunity, like never before, to shape commercial outcomes to benefit themselves.

Happy days, consumers.

The beauty here, for the customer that is, is that competitors may also gain access to this information, and try harder to appease the sentiment and win the business. This puts more relevant and desired products in the market for consumers to enjoy.

This also however creates urgency for businesses not yet leveraging big data capabilities to seriously consider doing so. Or risk being left behind.

By better understanding what your customers want, you can better design your strategy toward winning and maintaining their business, and ultimately improve your overall market share and bottom line. Because if you don’t appease your customers, someone else will.

 

2)   Optimise Operational Efficiency

A common strategy used by the world’s top FMCG companies is to use customer behavioural data to improve both supply-chain issues, and support for specific marketing initiatives.

These companies are already using big data to achieve significant savings in inventory costs, developing innovative products and improving targeting to increase revenue per customer.

For innovative companies, real-time monitoring and forecasting of events that impact business performance is a real advantage, helping them improve processes, increase margins, and save time and energy that is being put to better use.

By Increasing your operational visibility through early detection and resolution of potential network degradation, before it can negatively impact customer/user experience, you can help optimise performance for the short and long-term.

This kind of agility will become more and more important as the pace of change continues to accelerate.

So by structuring and controlling all the disparate assets that every operator possesses through utilising big data analytics and applying findings intelligently, you can start to shape what role you want to play in the digital economy. And more importantly, understand what steps you need to take to secure a foothold in the increasingly digitised future.

The key challenge nowadays is that with all this new data being created at an ever increasing rate, our algorithmic methods of extracting meaningful information is failing to keep up. The challenge is not necessarily the amount of data, but how we tag, monitor and mine it for information that we can knowingly take positive action on, and to the fullest extent.

There is also the fact that the market is experiencing a severe deficit of data scientists and engineers in a time of increasing demand, leaving companies to rely on new services such as Data Science as a Service (DSaaS), and other commercial off-the-shelf products, some of which are mentioned above.

That said, improved business efficiency has historically come with the invention and adoption of new technologies and methodologies; the pace of which is accelerating now more than ever.

On that note, my closing sentiment is this. Today’s big data is tomorrow’s small data. So be innovative, lead the way, adopt big data capabilities now and build a bright and secure future for your organisation in the digital age.

 

Hoani is an SMS Management and Technology Graduate Strategy and Advisory consultant specialising in cloud enablement and big data technologies. He’s a keen business and IT professional who believes all business decisions should be data driven, and therefore all organisations should strive to be data-centric. Hoani’s focus is to help organisations optimise cost, efficiency, and longevity by designing and implementing cloud-based/ data-centric solutions, coupled with sound business architecture that supports stable and agile growth in an increasingly tech-centric world.

 

 

 

 

 

 

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