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Analytics driving the sentient enterprise

By Shannon Williams, Tue 1 Sep 2015
FYI, this story is more than a year old

The continued data explosion and corresponding increase in analytical capabilities will drive organisations into becoming more sentient or intuitive.

That’s according to Teradata, who says the next trend in the analytics evolution is an ideal state known as the sentient enterprise.

The company says organisations will need be constantly listening, analysing and making business decisions based on data. 

The term ‘sentient enterprise’ is an idea that was thought of by Oliver Ratzesberger, president of Teradata Labs, and Professor Mohan Sawhney at the Kellogg School of Management at Northwestern University.

“The sentient enterprise can listen to data, analyse it, and make autonomous decisions at a massive scale in real-time. It will evolve constantly as its intelligence becomes more sophisticated,” explains Alec Gardner, general manager, advanced analytics, ANZ, Teradata.

“This journey depends on the company’s ability to embrace evolving analytics capabilities, beginning with today’s agile data warehouse,” he says. “As they unlock the full potential of big data and analytics, organisations will outstrip their competitors by making smarter decisions, faster.”

Gardner says most organisations have already started on the path to sentience. Teradata has identified five key stages that lead to fully autonomous decision-making.

1. Data agility Agile data warehouses create a balanced, decentralised framework for data. To take advantage of these, organisations have created self-service data labs and automatic, built-in governance. By analysing what people are doing in the data lab, organisations can learn from their behaviours.

2. Behavioural analytics Many organisations have changed their mindset regarding dealing with customer data. Behavioural analytics moves beyond transactional data (how many products were sold), asking different questions to gain new insights. It looks at all data points between transactions over time to formulate behaviours. Considering these behaviours instead of just transactions lets companies better understand how to interact with customers.

3. Collaborative ideation Working together to pool data and insights gives organisations a better view of trends and challenges. Self-service tools let more employees interact with data, broadening the pool of intelligence and letting users engage with information in new ways. This leverages the trend towards enterprise social approaches to decision-making.

4. Analytics application platform Enterprises will move from time-consuming, non-agile data movement and massive, centralised applications to enable smaller, self-service apps that can let users reproduce insights. This lets more people within an organisation leverage data to create analytical outputs and insights.

5. Autonomous decision-making Autonomous decision-making dramatically reduces the amount of time spent sifting through dashboards and mountains of data in order to make decisions. When companies leverage predictive technologies and algorithms to look at anomalies they can focus most of their time on decision-making instead of searching through data.

“Organisations can become more productive, scalable and agile if they improve data agility and adopt a behaviour-centric mindset,” Gardner says. “They must bring people together to increase collaboration, build repeatable processes and use algorithms at scale.

“When a business integrates all of these capabilities to think about, listen to and learn from data, it becomes a true sentient enterprise,” he explains. “Getting to this point takes knowledge and time. Each step can take a number of years but, as enterprises complete each step, they get closer to becoming a single, sentient organisation."

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