Published on the 10/06/2021 | Written by Heather Wright
And getting your organisation onboard…
The NSW Rural Fire Service has transformed volunteer deployment through its use of data. Macquarie Bank is using its data platform to improve client and employee experiences and get better risk management.
But data without a decision is merely a distraction and getting users to embrace data and analytics can prove challenging.
Case in point: The 32 percent of marketers in a recent Gartner survey who said a top reason for not using analytics was because it did not fit with their intended course of action.
“Data without a decision is merely a distraction.”
“As Issac Newton observed, an object at rest will stay at rest unless acted upon by an external force,” says Gareth Herschel, research vice president at Gartner. “Organisations are the same.
“We cannot simply tell people to use data, or build analytics infrastructure and hope people use it,” he says. “Data and analytics leaders must identify opportunities to change the way people think, until using data and analytics becomes a habit.”
Herschel, who was speaking at this week’s Gartner APAC Data and Analytics Summit, urged data and analytics practitioners for find agents of change within their businesses and develop a shared vision that identifies how analytics can help reach desired business outcomes.
“The reality is that D&A practitioners cannot do anything alone,” Herschel says. “Change must be driven by people and processes, not just technology.”
He also highlighted the need for organisations to build adaptive systems capable of evolving and keeping up with change and identified four technologies to enable organisations to automatically adapt to change:
– Data fabric to assist data integration
- Graph technology to help identify and understand complex connections between data
- Generative adversarial networks (GANs), which use simulations to identify processes improvements, and
- GPT-3, a natural language generation technique that will enable machines to tell data stories.
“As new sources of data become available they are automatically integrated into the data fabric. As we need to identify new connections, graph finds them for us. GANs allow us to develop and test thousands of options until we find best one and GPT3 allows us to reach everyone in our organisation and beyond,” he says.
“Only a handful organisations are using technology like this and even more bleeding edge such as quantum computing and DNA storage – but as Roger Bannister [who broke the four minute mile in 1954 after 70 years of people attempting the feat. Within 70 days of his success, the record had again been broken] showed as soon as someone does something clock is ticking until everyone else can.”
In line with that report about marketers reluctance over analytics, Herschel also noted a recent Gartner survey that just 40 percent of the respondents use data as their first choice approach for making decisions.
He says D&A leaders need to ensure data plays a role in every decision by reengineering the way decisions are made – looking for places to insert data analytics into formal process where decisions are being made, such as project plans or budget requests; and identifying hypothetical reasons an initiative my succeed or fail and checking the data for indications of the validity of those hypotheses were among his suggestions. Also an option: Encouraging influential people in the organisation to use data by feeding data points or visualisations they can use with their teams.
But if there are issues to be overcome in instilling a data and analytics culture within an organisation, there are also companies lining up to tell stories of their success.
At NSW Rural Fire Service – another of the conference’s speakers – a SAP-based centralised information system is providing the service with a transparent, real-time view of its 75,000 volunteers’ skills and capabilities, ensuring they can deploy the right skills to each crisis.
Emma Casime, NSW Rural Fire Service ICT project manager, says system enables every member, from front-line volunteers to top ranking executives, have access to real-time data when they need it.
The service is the largest firefighting agency in the world, covering 95 percent of NSW with 75,000 volunteers in more than 2,000 brigades.
“The volunteers all have different qualifications and capability and it was essential for us to have a real-time view of skills to help front line make the right decisions about who to deploy in an emergency,” Casime says.
In the past to access the data required a request to an analyst who would produce from the raw, unprocessed data a report which was immediately out of date.
Providing the information via a self-service portal makes real-time data easily available to those that need it and provides the ability to track and monitor KPIs from the state level down to brigade level, while also freeing up the analysts to work on different projects.
Combining the RFS’ own data with external census data from the Australian Bureau of Statistics is also enabling the RFS to gain a better understanding of the communities it serves and the volunteers within those communities.
“That gives you a lot of power,” Casime says. “We can see how we stand, how we compare, how many volunteers are in the communty and how many are volunteering for us.”
That can be used to tailor how RFS approaches the communities, and inform areas where it can put more effort into programs.
Meanwhile over at Macquarie Bank, a major data transformation journey has seen the bank simplify it’s data landscape, reducing costs and risks.
Ashwin Sinha, Macquarie Bank chief data officer, says the bank was focused on keeping things simple with the transformation and had three key goals – simplification of the data landscape, improving the client and employee experience, and to get even better at risk management and use of data for risk management.
It has since simplified from eight data stores to a single cloud platform, eliminating reports, dashboards and ETL (extract, transform, load) code that weren’t being used, and simplifying its database schema.
“That means we significantly reduced the data landscape we had to run, manage and support, reducing the cost of running the data platform by almost 50 percent and it has also improved overall resilience and robustness of platform and the risk management around it,” Sinha says.