- October 4, 2018
- Posted by: Peter Lunio
- Category: Analytics, Artificial Intelligence, Digital, social housing, value for money
(6 mins read)
Increasingly predictive analytics is being used to provide greater performance insights in the commercial sector.
In a recent AI survey by Deloitte, 60% stated that AI plays an increasingly important role in driving business strategy & performance.
In addition to this, recent claims have been made that the sector needs to be more data-driven!
As Mark Henderson CEO Home Group commented in his blog on June 17:
“We’re all trying to make better use of our data, to understand the cost of the services we deliver, and how to target our resources to make the biggest difference for our customers and the communities in which we work. However, we can’t have a full understanding of our performance without knowing how others are doing – by sharing our data, it becomes much more powerful.
We at IwP were, therefore, intrigued as to how widespread the use of data analytics is, and the level of AI maturity there is in the sector.
So, in the summer of 2018, we undertook a short survey to find out how the sector was shaping up to the AI world.
- How Important is AI?
We were trying to understand out how important AI is to the sector both now and in the future.So in response to our question, “How important do you feel the use of predictive analytics is to gain performance insights currently?” The majority of the respondents said yes it was very/important for both their association and the sector. (See below)
We then asked an additional question which was, “How important do you feel the use of predictive analytics will be to gain performance insights in 2020?” (Fig2) The level of importance showed a significant increase to 80 %.
It is clear that most respondents thought overwhelmingly that AI was very/important to their association and the sector, and increasingly so in the next few years.
Insight: So predictive analytics as a sector initiative is definitely on the up.
- Decision Making
We wanted to find out how much data was driving executive decision-making.In response to our questions on” how your association would best describe the way, you make executive decisions?”
Worryingly, almost a quarter of respondents stated that decisions were rarely data-driven. (Fig 3)
Conversely when we asked the question, “When making strategic decisions what do you mostly rely on?” 47% said they rely on experience and intuition, which seems to contradict the previous question. (Fig4)
Insight: Confusing picture as to whether decisions are data-driven.
- AI Capability
We looked to try and identify the level of AI capability and maturity associations have and the extent of usage of their data.
Two-thirds thought their associations were developing their AI capability, but 13% had only a basic capability. (Fig5)
This is supported by the level of technology respondents claim to have available in relation to their technical capability, with 47% having only basic reporting/predictive tools. ( Fig 6) Fig6
Over a third rated their association as not being particularly effective in how its organisation utilises its data that it has currently, to provide deeper insights that will improve the performance of their association.
What is encouraging is that 80% of respondents stated that increasing the use of AI is an initiative that their organisation was keen to develop.
The problem appears to arise when we asked, “Do you believe you have the resources and expertise in your association to improve the use of AI?” Three-quarters responded with no/maybe. Over a third of respondents seeing this as a CEO/FD led initiative.
Insight: we draw from this is associations have few of the analytical tools to deploy to assist in making more data-driven decisions nor the resources to do so!!!
- Outcomes and Benefits
So what are the benefits, outcomes and additional insights that respondents were hoping to gain from their AI initiatives? The question we asked was, “What better outcomes could be achieved by the greater use of AI in your association?”
The respondents highlighted, Reduction in Costs, Improved Innovation, Speedier Decision Making, Increased Customer Satisfaction, and Improved Forecasting as the key outcomes that they sought improvement in. ( Fig7)
This matches the recent survey done by PWC 2017.
We also asked, “In which areas of the organisation did they feel their association needed to generate more analytical insights?” In order of priority:
- Housing Management 76%
- Repairs & Maintenance 70%
- Asset Management 66%
- Customers 56%
The best is yet to come. The majority of respondents feel that AI will become more important to their organisations in the next three years. Two reasons there is plenty of room to grow: a great deal of data is still not used for decision-making, and many organisations have the only rudimentary analytical technology.
It’s clear from the results that the sector is awakening to the use and benefits of utilising a data-driven approach. It seems that AI is growing in importance and the sector is keen to develop it further. With innovation, speedier decisions and cost reduction seen as the key outcomes, particularly in Housing Management, R&M and Asset Management.
The concern we have is the level of capability and analytical tools that associations tell us they have at the moment is clearly not sufficient to deliver the benefits they are seeking. Without a major investment in both resources and tools, most associations will be left behind those that embrace a more data-driven approach.
If you would like to take part in our AI survey to benchmark your association then click on the link below.
To read further on an introduction to AI and developing an AI strategy for your association then read our articles by clicking on the following links.
5 min Guide To AI.
AI some considerations for Social Housing
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