Case Study
Microsoft
Azure
Healthcare

Data & AI for CRM

June 28, 2019

Data & AI for CRM in the aged care industry

About the aged care industry

The aged care industry is in a highly changing state. Growth is being achieved by those organisations who aren’t just delivering clinical care but a more comprehensive suite of services that provide holistic care, considering mental and social health. An ageing population also contributes to organic growth. Funding models, that previously provided predictable revenue streams, are changing and organisations must differentiate in a more open market that demands greater focus on customer value and retention. To set themselves apart they need to find new and innovative ways of delivering better services to their customers, whether in purpose-built facilities or their own home. Audit and compliance represent significant challenges, self- and industry body-initiated investigations, including royal commissions, mean governance is a critical consideration that organisations must provide significant resources for. The introduction of e-health records and other government-initiated innovations creates a fertile environment for bi-directional data exchange or shared core-systems in the future.

What role can technology play?

Dynamics 365 is a modern, modular platform that enables businesses to engage customers, optimise operations and empower employees. With thousands of tables and entities, it provides rich datasets for analysis, however companies need to unlock the value of that data as quickly as possible. By implementing automated, robust patterns that combine this data with a multitude of other datasets, the ‘time-to-value’ can be brought down considerably. Carers, who spend a significant amount of time on admin tasks and accessing information about the customer, can be enabled with access to centralised, standardised reporting and information, on a mobile device. Allowing carers to access the customer’s history, health, loved ones, hobbies and interests, on demand, reduces manual effort and helps them to deliver a better quality of service while creating a more compelling, customer-driven, product. Customers who do not feel empowered with their own care, and their families, who often rely on slower communication channels, can (with consent) be enabled with smart devices, cameras and GPS devices, or access to chat and other instant communication technologies that provide greater visibility and immediate status feedback. Aged care carries inherent risk to customers due to their physical impairments. To prevent incidents and reduce customer risk, predictive analysis and Machine Learning algorithms that correlate incident events, can highlight processes with increased risk and drive policy change for front-end processes. The management of assets in care facilities creates another administrative overhead for staff. Integrating with maintenance suppliers’ systems allow the automation of regular maintenance schedules that increase asset life and ensure reliability for their users.

The solution

Seisma, with years of experience integrating Dynamics and data solutions, delivered a modern analytics platform, in Azure, where Dynamics 365 combines with many other data sources to deliver a range of solutions across the business intelligence spectrum, including:

  • Automation – automated reports that provide answers to regular questions much quicker
  • Ad hoc Analysis – allow the business to derive rapid business value from new questions
  • Predictive Analysis – to predict incident events and reduce risk
  • Advanced Analytics – Machine Learning algorithms that discover previously unknown correlations between events

The client approached Seisma to deliver some insight into how best to spend their marketing funds. Using a combination of Azure Databricks and Cognitive Services, we analysed and forecasted occupancy rates across all their facilities, which has enabled them to increase localised marketing activity in lower-occupancy areas.

*This case study is sourced from acquired company Data Addiction.

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