Change is the only constant, and it’s only accelerating. Technology is taking us closer and closer to the futuristic worlds we once only imagined in science fiction, but questions remain. How is innovative technology changing the way we do business? How will it continue to change in years to come?
In the current climate, operational efficiency and business agility are more important than ever to support modern business innovation. As global markets combine with competitive pricing pressures to place greater stress on maintaining margins, organisations must seek the efficiencies needed to protect market share.
Investment in big data has risen in 2016. That’s according to tech consultants Gartner which reveals that 48% of companies invested in big data this year, an increase of 3% compared to 2015. Planned investment in the next two years is predicted to fall, however. The issue, according to Gartner, is not so much the data but how it is used. 85% of companies who invest in big data remain in the pilot stage as projects fail to progress beyond the initial commitment.
There’s been a lot of discussion across the enterprise IT and financial analyst community about the long term economic viability of the SaaS business model. And the enterprise IT community continues to debate the merits of the various flavors of SaaS architectural and infrastructural models.
The reality today is that most enterprise applications are well on their way to being cloud based. We’ve seen it with simple workloads such as HR and payroll, travel and expense management, and in the last decade we’ve seen the cloud as the new normal for customer relationship management (CRM) deployments.
Data driven recruitment has a significant, positive impact on talent management strategies and business performance. As technology becomes more sophisticated, AI is playing an increasingly essential role in decisions made around hiring and is used by brands such as Facebook as an integral part of the screening and assessment of candidates.
This article examines its ongoing effect on the jobs market and the ways in which HR can harness its advantages to better understand, improve and predict hiring needs and potential problems.
First there was big data – extremely large data sets that made it possible to use data analytics to reveal patterns and trends, allowing businesses to improve customer relations and production efficiency. Then came fast data analytics – the application of big data analytics in real-time to help solve issues with customer relations, security, and other challenges before they became problems. Now, with machine learning, the concepts of big data and fast data analytics can be used in combination with artificial intelligence (AI) to avoid these problems and challenges in the first place.