Akesh Lalla, country manager, SAS South Africa.

Akesh Lalla, country manager, SAS South Africa.

There can be little doubt that the market is facing a slew of innovation-based disruption, which is arriving from all quarters. This, in turn, is leading to a surge in technology-based innovation coming from non-traditional sources, like Tesla, Netflix and Purple, which is severely impacting traditional business models.

This innovation-based disruption is the basis for the analytics economy, explains Akesh Lalla, country manager for SAS South Africa, who points out that this economy is the unifying fabric that delivers the full value of innovation-based disruption.

"The analytics economy combines data analytics and collaboration with rapid, applied insights, to enable enterprises to harness new technologies in a way that creates this innovation-based disruption," he says.

"Cloud computing, open source, mobility and social media need to be harnessed properly, in order to be able to access and consume all types of data and to be able to use the best analytical methods in order to create new insights."

Lalla points out that, although not exhaustive, the following industries are impacted by the current market disruption, and will need to evolve if they are to survive in an analytics economy. "The list includes banking, insurance, communications and retail. However, we must not discount the impact this economy will have on the public sector.

"With banking, the most important trend currently is customer experience, because achieving success here is the primary driver for increasing revenue. Banks need to utilise real-time analytics to understand customers' unspoken needs during their journey through digital channels, and then act on these through an optimised, next-best communication in-session that is targeted for a segment of one.

"From an insurance perspective, it must be remembered that fraud impacts every insurance company, and the general consensus is that suspicious activity is increasing. Moreover, the tactics used by fraudsters are becoming more sophisticated. The fight against fraud is taking place on many fronts, and insurers must increasingly leverage analytics to identify patterns that will help them to combat opportunistic and organised fraud across all lines of business."

In the communications arena, continues Lalla, companies can no longer rely on their hardware-based network infrastructure to meet market demand. Bandwidth continues to come at a premium, while data consumption continues to increase exponentially.

"The need to transform has brought new technologies to market, such as software-defined networking (SDN), which enables digital transformation. At the same time, the explosive growth of social media has elevated the power of the consumer and forced communications companies to place customer experience at the forefront of enterprise decision-making.

"Retailers need to bring a seamless experience to their consumers. This requires a single view of the customer throughout all channels. This also requires the ability to have visibility of the supply chain and inventory for sales associates and customers to allow the consumer to choose the best and most efficient delivery method, whether that be in-store, delivery or a combination of purchase in one channel and deliver in another (ie, buy online, pick up in-store: BOPIS). This shift has greatly expanded the landscape of where the shopping journey begins and ends, and has moved retail into a 24/7 always-on schedule."

"CPG (consumer packaged goods) manufacturers can no longer afford to run plants to capacity, then discount products to move inventory. This common practice drives huge inventory costs and creates missed opportunities at the point of sale. First understanding demand, then managing it and balancing supply, is now necessary in most markets. CPG companies are starting to turn to predictive analytics to refine decision making. They are trying to mine massive amounts of historical point-of-sale and promotions data, integrated with real-time data from social media and weather forecasts, to predict daily demand by store and optimise assortments and promotions in order to maximise sales and profitability. Adopting this approach has required companies to develop new algorithms to integrate near real-time demand data with traditional forecasts and implement new technology systems to facilitate data sharing with customers and distributors."

"Finally, the public sector, unlike private business, is not focused on profit and loss statements and returning dividends; instead, government serves as the stewards of the tax payers' money. Stewardship, the responsible and careful management of something entrusted in one's care, demands that government be able to demonstrate its effective and proper application of this tax to the services and programmes that provide the greatest benefits to its citizens," states Lalla.

Furthermore, he adds, with the rapid growth of government programmes and their associated data, the ability to leverage and analyse big data from across the government enterprise is critical in providing the necessary insight to ensure effective and efficient government operations.

"These are just some of the larger sectors being impacted in this way, and one thing that is certain is that data analytics will only gain momentum moving forward. In fact, it is safe to say that reliance on business intelligence (BI) and analytics now likely outweighs strategy as the key requirement in business planning," he concludes.

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