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Therefore, it’s more important than ever to ensure that business owners and managers are doing all they can to understand how their business may recover, and perhaps change, in the future. One of the ways in which this can be achieved is through the use of technology such as artificial intelligence (AI) and business analytics.
When most people think about AI, they tend to think of robots and science labs in which scientists develop AI for large companies. In reality, it’s possible for small and medium-sized businesses to take advantage of AI in order to develop analytics, which results in a better understanding of their market and to model potential future scenarios.
Sport consumption has seen a huge increase in recent years. With record viewing numbers for the likes of Premier League last season, and a novel willingness from consumers to pay for exclusive online content. As a result, sports is a lucrative source of revenue for network and programming brands.
Alongside this increase in popularity, modern television offers fans a more up close and personal experience at a fraction of the cost compared to attending live sporting events. Viewers can watch from the batter’s eyes, and encounter the huge right hand made by MMA fighters. In many ways, the viewing experience has evolved to become what Doug Kramon, ESPN’s senior director of fan support and customer care views as a ‘virtually there’ experience.
Business changes all the time, but advances in today’s technologies have accelerated the pace of change. Machine learning analyses historical data and behaviours to predict patterns and make decisions. It has proved hugely successful in retail for its ability to tailor products and services to customers.
Unsurprisingly, retail banking and machine learning are a perfect combination. Thanks to machine learning, functions such as fraud detection and credit scoring are now automated. Banks also leverage machine learning and predictive analytics to offer their customers a far more personalised user experience, recommend new products, and animate chatbots that help with routine transactions such as account checking and paying bills.
On the face of it, there is little to unite the construction and tech sectors. Superficially at least, the construction sector provides a classic example of ‘waterfall management’: strict plans are formed at the outset of a project, and resources are fixed in place, even though the finished product might be three years away. It is a right-first-time, zero defects sector with detailed dependency scheduling. The tech sector, by contrast, is known for its not-afraid-to-fail, agile mindset, eschewing scheduling for creativity. Tech and construction, then, would certainly appear to be strange bedfellows. Times are changing. The proliferation of Building Information Management platforms on construction sites up and down the country neatly demonstrates that tech really can be embedded into the foundations of a building, and by extension, the construction sector. But how do we further embed the two, often conflicting, cultures?
Internet-enabled devices have led to an explosion in the growth of data. On its own, this data has some value, however, the only way to unlock its full potential is by combining it with other data that businesses already hold.
Together, pre-existing data and newly-minted IoT data can provide a full picture of specific insights around a single consumer.