Make smarter decisions with AI-powered business intelligence

In today’s competitive real estate market, as the volume of data continues to grow across organisations, highly effective data management and business intelligence (BI) processes can provide significant advantages. 

BI has been around for a while now but in the last decade, the way we interact with and consume BI has dramatically changed. At its core, it acts to transform raw data into actionable insights, helping organisations make informed decisions. But arriving at these actionable insights takes a well-defined data strategy, backed by commitment from stakeholders across all levels of your organisation. 

In this blog series, we’ll be digging into the detail of how you can make smarter business decision with AI-powered insights. We’ll look at:  

• Data democracy  
• The key elements of a data platform 
• Ways to improve storytelling through data visualisation 
• How to use AI to interact with your data  
• How MRI Agora Insight can drive your business decisions

What does a successful data strategy look like?

Organisations will define their data strategy differently according to their business requirements, but there are several crucial elements to help drive a successful strategy. Consideration to these elements will help ensure adoption and integrity when dealing with internal and external stakeholders throughout the process. It is also important to define from the onset what data success looks like for your organisation – and not losing sight or compromising on these success metrics.  

1. Data Governance

Data governance is the cornerstone of a successful BI strategy to ensure data security, continuous quality, and privacy compliance. 

• Security and Auditing: Robust security measures such as establishing access rights will safeguard sensitive data and establishing regular audits will help to ensure security is being maintained. 

• Quality Management: Utilising technologies, procedures and correct training for staff will help to maintain data quality, through regular cleaning and validation processes. 

• Data Ownership: Assigning clear ownership for different data areas will help with accountability and enforcement, with respective data owners responsible for data quality and accuracy. 

MRI Software and Data Governance
The MRI Agora platform has globally adopted the OSCRE Industry Data Model™ (IDM) to help clients improve strategic decision-making and reporting and easily integrate disparate software applications. As real estate organisations seek to leverage multiple PropTech applications to drive business success, industry data standards will be key to facilitating integration with existing technology and enabling rapid adoption of future innovations, including Artificial Intelligence (AI).

2. Data Integration and Warehousing

Data insights become even more valuable when integrated across multiple data sources, so organisations can begin to see patterns, trends, interactions, and financial information in one place. Effective data integration involves centralisation of your data, into a data warehouse. This central repository then becomes a structured environment for data interrogation and analysis. When thinking about solution integrations and preparing data for warehousing, consideration should be given to: 

• Data preparation: Review and cleansing of data into a consistent format and structure will help to facilitate smoother integration. 

• Standardisation: Use standardised data governance models to ensure uniformity across datasets. 

• Optimising storage: Consider a warehouse design that offers scalability to comfortably store and retrieve large volumes of data, based on current and future needs. 

3. Data Platforms

Deciding on a data platform is the final step in a data strategy, providing the foundation for reporting, predictive analytics, AI and other advanced analytic requirements. We recommend scalable platforms, to support your needs as the organisation grows. Platform integration with tools such as Power BI is a must, to aid visualisation and analysis of data. In-house IT teams or service providers should also monitor the platform routinely for performance.  

Implementing a data strategy

“Before you can actually work out how to get to where you want to be, the hardest part is working out where you are now.” 

Ian Niblock, Senior Director Product Development, MRI Software 

It’s important to assess the current state of data and capabilities within the organisation. This may include building a comprehensive catalogue of systems and data sources, infrastructure review and current stakeholder involvement – potentially identifying any gaps to address.

Break down the strategy

Create a project plan around your strategy, with key project milestones, task breakdowns and timelines defined. This will help organisations execute on manageable tasks and review in stages as small parcels of work – rather than an overbearing project in its entirety. This approach is not so dis-similar to a software implementation; define small achievable projects with clear objectives and timelines.  

It’s important to focus teams on high-priority tasks that deliver the greatest return on investment, as this will help to capture buy-in from the on-set if you can see payoff straight away. As you work through the stages, use every opportunity to showcase the immediate benefits – helping to keep the wider business informed and connected to the project.

Gaining Buy-In

Securing buy-in from all levels is crucial and helps foster a data-driven culture for the organisation. Engage both top-down and bottom-up and educate with use cases to demonstrate the benefits and value of a data strategy. Be clear on specifics on how BI can make their world better.  

Tip: Be prepared to address the ‘why’ question from stakeholders, using specific tangible benefits will help.   

Cost Management

Implementing a data strategy can be costly, so managing resource allocation and expenses is important. Evaluate third-party vendors for cost-effective solutions and support, and ensure solutions are scalable to avoid unforeseen costs in the future as and when data volumes grow.

Organisations vary in terms of their progress and investment in data strategies. Some choose to do this in-house and can spend millions of pounds to build platforms, but internal resources are key to ensure platforms can be maintained and supported as data requirements grow. Maintaining platform environments is an expensive exercise and the more data you put in, the more systems you connect, the more resource and expense you’ll incur. 

Keen to know more?

Interested to hear how MRI Agora Insights can help your business? Book a discovery call with our friendly team today. 

Keep reading

This article is the first in a series. Continue reading to discover the importance of a data democracy, and how to achieve this in your organisation.