“Cloud computing is empowering, as anyone in any part of the world with an internet connection and a credit card can run and manage applications in the state of the art global data centres; companies leveraging cloud will be able to innovate cheaper and faster.” -Jamal Mazhar.
The post-modern information age with its emphasis on materialism and the rapid consumption of goods and services has forced and is pushing traditional retailers, both large and small, into diversifying and evolving into retailers that can meet the consumer’s excessive demand for instant goods and services coupled with the challenges of the digital age.
On 2 August 2016, the InformationAge.com published an in-depth discussion on the challenges that traditional brands and retailers face due to the rise of the online consumer trend, the impact of the rapidly changing consumer behaviour, and the fast-paced technological revolution.
The takeaway point of this discussion is that brands and retailers have to adapt and change to embrace this new age. If they don’t and choose to stay in their current format, there is little chance that they will be in business for too much longer. The article backs this statement in the following way by stating that “it is safe to say that brands that fail to adapt won’t survive long. The death of the well-established retailer is just the beginning. The death of the well-established retail model is underway. And the winners will be the businesses that think digital from the top down.”
The role of Big Data in the modern retail business model
One of the ways for retailers to survive the death of the traditional retail business model is to become a data-driven organisation. However, before we look at the impact the evolution into a data-driven company will have on the organisation’s bottom line, let’s look what the term “data-driven company” means.
Simply stated, a data-driven company is an organisation where every decision-maker has free and unlimited access to the data which is required to make an informed decision. Adi Gaskell, in his article titled “Becoming A Data Driven Organisation“, notes that “making data based decisions makes instinctive sense, and evidence is mounting that it makes strong commercial sense too.”
Furthermore, research conducted by the McKinsey Global Instituteindicates that data-driven organisations show the following probabilities when compared to a non-data-driven organisation: They are twenty-three times more likely to acquire customers, six times more likely to retain these customers, and nineteen times more likely to be a profitable organisation.
Therefore, it makes sense to conclude that Big Data is essential part of the answers to the questions that business decision-makers ask.
Cloud Computing: Enhancing the role that Big Data plays in the decision-making process
The Information Age, as well as the improvement in modern computing technologies (both hardware and software), allows companies to generate and store large amounts of data such as customer-related, sales, and supplier data. Additionally, organisations collect significant amounts of analytical data on consumer trends and consumer behaviour from social media as well as from tracking user interactions with their eCommerce store.
This data is typically stored in different databases on different in-house servers (or in data centres); however, for everything to be analysed and interpreted together, the data from each database needs to be uploaded into a single data warehouse.
The computing power, as well as the size of the storage facilities required to run a data warehouse, is astronomical. The cost of purchasing and maintaining these data servers is just as huge. Additionally, buying large servers to run a data warehouse limits scalability, and allows for extended periods of server downtime.
Therefore, the question that begs is how do organisations solve their data warehousing challenges?
The answer can be found in the modern Platform-as-a-Service cloud computing offerings from companies such as Google, Microsoft, and Amazon. All three companies offer similar functionality in that they offer rapid scalability versus reduced cost.
In practical terms, organisations get to choose the size of the storage and computing power needed to manipulate and analyse their data in a matter of minutes rather than having to purchase, upgrade, and maintain their servers and network infrastructures. For example, Google Cloud’s business model charges per minute of compute time based on the number of CPS and RAM chosen. Once the data analysis and manipulation is complete, the job ends. Thus, translating into a substantial saving on the virtual hardware acquired versus the actual cost of procuring the physical hardware with the same storage and compute engine.
There is no doubt that the cloud computing or Platform-as-a-Service is the solution to an organisation’s Big Data analysis and manipulation challenges. Effectively, the more data that is analysed, the greater chance of providing in-depth answers to the business decisions that need to be made as part of the modern retail business model.