Robotic Process Automation
Robotic Process Automation (RPA) has the potential to radically improve operations
Robotic Process Automation (RPA) is the use of software robots (not real robots!) to automate data processes. RPA can be configured to take different types of data from diverse systems, manipulate the data, and deliver a programmed output.
- Cost efficiency: Adding RPA robots to complement the human workforce can reduce costs because robots are cheaper than humans
- Improved analytics: RPA has the capacity to deal with more data from more diverse systems than humans, enabling better data analytics for more productive decision making
- Process and productivity improvements: Reduce the amount of time doing repetitive work and reduce the prevalence of errors, through automating standard data processes
- Enhanced customer experience through improved reporting: Automating more accurate, granular and quicker reports can improve the experience of clients, customers and internal stakeholders
Oli Farago, CEO and Co-Founder of Coyote, shares with CBRE’s Nick Wright how the property industry is finally waking up to the benefits of tech, and how Big Data is at the heart of that change.
Coyote is the proprietary in-house software for M7 Real Estate.
RPA can bring cost efficiencies to investor and occupier reporting processes, across assets and portfolios across the globe.
The true power of RPA will be unlocked when businesses develop structured data strategies. This is particularly important for global occupiers and asset managers or landlords with global portfolios. RPA especially when using ‘big data’, can enable more advanced analytics that can uncover opportunities for more profitable business and location decisions.
RPA, and any successful data initiatives, will require proper collaboration between the real estate facing business function and the IT department. RPA is a middle, though not necessary, step towards Artificial Intelligence, so investment decisions should take account of this – it requires a short, mid and long-term digital and technology strategy.
RPA can enable your human workforce to be more productive, through unlocking their time. This affects employees, corporate real estate function and asset or portfolio managers.
Hoxton Analytics CEO and Founder Owen McCormack and James Pearson from CBRE explore the benefits of Big Data for retailers, and the insight to be gained from better data collection and analysis.
Hoxton Analytics is an award-winning start-up that helps high-street retailers make better business decisions by providing them with accurate data about their customers.
RPA can enable more effective portfolio and building management, through identifying where inefficient processes or assets are in a shorter period of time. This enables more productive decision-making.
RPA could have implications for use of buildings depending on whether companies outsource the activity or keep it in-house. If it’s the latter then the amount of space dedicated to servers may increase. This could potentially change the investment characteristics of property, but also the design characteristics from a workplace point of view, in terms of the efficient design of space.
RPA can be cheaper and more accurate than the human workforce if deployed properly. It could have implications for the nature of occupier demand as well as for the investor and corporate real estate functions itself.
RPA can enable better customer experiences through higher quality and more responsive reporting. For fund managers this means better investor relationships.
Implementing RPA can improve employee experience through removing tedious and clunky process-driven tasks from their day. Employees can use the freed-up time to engage in more intellectual, cognitive tasks, not only improving productivity, but improving engagement and fulfilment.
Peter Bredthauer CEO and Co-founder of PRODA reveals how big data is the most valuable asset for decision making in the real estate industry, and the challenges for commercial property firms in gathering, organising and analysing their data, using machine learning.
PRODA harnesses the power of AI to capture and standardise rent roll data, priming it for reporting, analysis, storage and exchange.
- Objective: Reduce the manual labour time of employees and improve reporting efficiency
- What they did: Deployed RPA robots as a virtual workforce to complete the manual work
- Outcome: Reporting labour time has been reduced from 1.5 days to 6 minutes. A quicker and more accurate reporting process. Employees time has been freed up to complete more cognitive work.
- Data intensive: If you have data intensive processes, these are ripe for automation using software
- Repetitive and rule-driven manual calculations: Repetitive data processes are easily executed by machines rather than humans as all of the rules can be pre-programmed. The outcome is a quicker, more accurate output
- Multi-system: RPA can be perfect if you get similar data from a variety of systems. Rather than humans fetching the data manually on a regular basis, why not programme robots to do it automatically?
- High-error rates: Humans can be susceptible to making mistakes which can be costly. Reducing error rates can save time and potentially lots of money.
Source: EY, 2018 and CBRE, 2019
- What is RPA? (CIO, 2018)
- What are the potential uses of RPA in Real Estate? (EY, 2018)
- What are the cost savings of RPA? (Deloitte, no date)
- How can you learn from other industries? (Deloitte, 2016)
- RPA is only one component of wider change – how could it affect your business? (KPMG, 2017)
- RPA can also enable more advanced analytics. How can you learn from the residential sector? (McKinsey, 2018)
- RPA is more than just ‘automation’. It can lead to “Operations 4.0" (McKinsey, 2017).
- The challenge of proving ROI is still very real (McKinsey, 2016)