Adapting to changing technology

The Data Challenge from a Human Perspective

Carolyn Trickett blog The Data Challenge from a Human Perspective

Wednesday, 7 February 2018

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Adults make around 35,000 decisions per day

How many decisions do you think you have made today? Recent studies show that adults make around 35,000 decisions per day, ranging from what to have for breakfast to important life and business decisions. But with so much information available to us all now, how can we be assured that we are making the best possible decisions?

What is the difference between Data and Information

So, what is the difference between Data and Information?

Data is raw, unorganized facts or figures, but it has to be processed, interpreted, organized, structured or presented if it is going to be meaningful or useful – that’s what makes it information. If the data is not put into context, it means little or nothing to a human.

The Human Experience

I'm going to share some of my thoughts with you the challenges we face from a human perspective, with all the new smart building technology that is becoming available to us. I will provide some insight into how to overcome those challenges.

I’ll talk about information overload, getting meaning from data, and the new skills required in the building management industry.

Noise is the enemy of information

I'm a bit of a google addict. Whenever something comes up in conversation or whenever people are debating a subject that I am unfamiliar with, I just love googling the subject matter and finding out the facts. I feel compelled to cross reference the information I discover to make sure the information I find can be corroborated by a few different sources.

How many times have we all thought "how did we ever work this stuff out before the internet?" How did I ever find a restaurant, catch a cab, book a flight, claim on health insurance?

We have access to all this data, but it doesn’t always translate to information value. Often, it is actually just noise.

The human race feels smarter than we used to

Because of our instantaneous access to information, we perceive our own intelligence as a human race has increased. We feel smarter than we used to. In fact, in 2009 a team of UCLA researchers found that the use of the Internet can double the brain activation, increase efficiency of cognitive processing and actually lead to changes in the way our brains store information.

But this increase in intelligence, whether perceived or actual, comes at a price. The plethora of information which bombards us all day, every day, introduces an enormous layer of stress.

We know that the information is continually available, it keeps on coming through, it multiplies - and we feel anxiety if we are prevented from knowing about it instantaneously. We struggle to distinguish information value from information noise.

Smart buildings generate massive amounts of data

We all know Smart Building Technology generates massive amounts of data. People working in the building management industry are already inundated with data and decisions to be made all the time.

In many ways the introduction of the smarts – the Artificial Intelligence and Machine Learning into building technology - has the capability to take away many mundane tasks, taking away the need for human intervention, even remove the need for us to think about some things.

But it also introduces a whole new layer of activity for humans - the need to analyse the data and turn it into information, and use it to make decisions.

Information Overload

So what is information overload? Many of you will be feeling it right now after nearly a full day at a conference. It’s not a new concept.

In the 15th century, the invention of the printing press sparked a spate of fear about the abundance of information, because the constant supply was considered to be distracting for scholars.

In the 18th century, the problem was associated with the overproduction of books - comparisons to an epidemic.

And then in the 1960s, the term Information Overload was coined - it started to crop up in relation to computer processing capacity as well as the human ability to absorb information.

Most humans can only handle about seven discrete ideas at any one time

Around the same time, a psychologist at Princeton University (George Miller) came up with a concept that most humans can only handle somewhere around seven discrete ideas or pieces of information at any one time.

In 1970 a book called “Future Shock” was released, about problems in society as a result of things changing too fast.

Email didn’t even exist back then. The first email in history was sent in 1971, and it was another 20 years before the first website was created. The iphone was created 16 years after that!

The Information Storm

I don’t think anyone could have foreseen the storm of information that humans are constantly being bombarded with today. The weather and the tripview and the uber the fitbit and the coffee app and the new house that just came onto the market.

There are a lot of buzz words around now too – infobesity, information fatigue syndrome and my favourite – infoxication.

But let’s talk in real terms. In my experience in the world of property and technology, I see three main contributing factors of big data towards Information Overload – Quantity, Quality and Timing.

Too much information

Most modern commercial office buildings have over 100 thousand data points, but the reality is that you can only probably get useful information from about 100 of them. So in order to get a good outcome, you need to work out how to filter the data and make decisions about what information will be useful.

Most people feel a sense of overwhelm when they see massive amounts of data. There's so much but where do you start?

At JLL we spent a few years and many dollars building a digital reporting platform. It is a comprehensive, interactive online tool that aggregates and presents data from 3 different source systems. We provide the dashboards to our clients – 6 modules, 17 pages, over 40 graphs and dials. There is so much information in there! But do you know what is one of the most frequently asked questions, when people first see it? “can I get a 1-page report?”. Because they actually only want to know 3 things, maybe 5. We give them 3 screens for looking at tenant information and they ask “can I have a snapshot”?

We use this tool to do benchmarking. Hundreds of properties, thousands of leases, a plethora of invoices all go in to the system to get analysed, and the outcome is one blue box representing JLL benchmarks, one green box representing industry benchmarks and one RED DOT to represent the building you are looking at. Now that’s an understandable amount of information.

Apply that same concept to smart buildings, where you have sensors that can capture millions of bytes of data every day. When you start to get useful information, even when you summarise it into less pieces of information, do you have the time or the money to action them all?

There's no point getting a list of 100 faults that need to be fixed. Most asset owners don't have unlimited budgets to spend fixing every single fault. It would be better to distil it down to a list of 5-8 things to focus on. Some of our clients have had systems aggregating their BIM data for 4 years and are still just getting around to fixing some of the things that they found.

Poor quality information

This can happen when you try out new technology for the sake of it.

One of our clients was setting up remote monitoring sensors on their buildings. They were sending information back to our dashboard about temperature, vibration, pressure. But they didn’t spend enough time thinking through the outcome – what they wanted to find out. So we ended up with data that didn't tell the full story. The water temperature from the chiller was too high, but we couldn't tell if it was actually switched on.

Another facet to this dilemma is that you often don't know what you want to do with the data, until you have seen it.

A client who installed sensor lights, so that they could analyse the occupancy rates of meeting rooms. It was amazing to see how often the meeting rooms weren’t actually being used. (That definitely was not our office!)

But the project didn’t achieve very much. They wanted to feed the information to the meeting room system so they could switch the room to available if it wasn’t being used, but the lights they chose had a closed protocol, so the data could not be integrated with the meeting room system. They knew their rooms were under-occupied, but couldn’t do anything about it.

Bad timing of information

Timing the receipt of information is also important in determining whether it is useful, useless, or distracting.

For example, most people in this room have access to email on their phone. A large majority will check it compulsively today. But usually, if you’re in a situation where you need your phone to keep track of email, that means you’re in a situation where you can’t readily respond. You’re in a meeting about something else, or you’re on the road.

If I checked my emails right before giving this talk, anything I found out would probably just be a distraction, I’d be better off not know about it. Knowing that there is something you need to respond to but can’t, actually increases the stress level on your brain. It’s one more thing to remember to do or say or think about later.

So the information that the fridge at a retail warehouse is malfunctioning is very valuable, as long as you find out soon enough, before all the food goes bad.

Smart building technology is changing the way we operate

Smart building technology is changing the way we operate buildings, and they are also changing the human skill sets we need to operate them.

To be successful we need to understand the human experience. No matter how smart our buildings are, we still have people managing them and making decisions about them. So we need to understand the impact it is having on them, and how to maximise the positive aspects of that impact.

So as we approach the world of smart building technology, there are two considerations to keep in mind to ensure success. Getting meaning from the information, and getting the right people.

Getting meaning from the information

To get meaning from the information available, it’s important to consider WHY are we spending money, WHAT are we going to do with the outcomes, and WHEN will the information actually be useful.

There’s a lot of tools out there than can help to visualise, analyse and interpret the data. But you probably won’t have someone looking at it all day, every day.

JLL example – we can’t just install a monitoring platform and start inundating our building managers with a flood of information. This just adds another layer to their job, and they are already busy coordinating all the activity going on in their buildings. So we have had to to look for ways that the tools and information can free up their time from other tasks, so they actually have the capacity to use it.

At JLL our Command Centre is focused on the goal of our team members knowing what is happening without having to be there. We are looking for ways to automate and streamline the property maintenance process. The first step is to enable a remote team who only visit the site if a fault has occurred. Save time on travel and inspections that reveal nothing, only to have a fault occur a day later.

If that is the reason for getting the data, then we probably only want the information if it’s a real fault that needs to be actioned. So we need to adjust the systems to ensure they are only telling us that and not everything else.

If you don’t know the end game before you start the work, then it can end in conflict and disappointment, where people on the ground are bombarded with information but not empowered to do anything with it.

Finding the right people

Name one thing that most people are scared of? Statistics.

It used to be excruciating. My friends studying Psychology at Uni were terrified of the statistics computer. It was a nightmare, clunky slow and impossible to understand. All that has changed now with the business intelligence tools available. Anyone with excel skills can become an amateur data analyst.

When I first started at JLL, there was so much administrative work. Paper shuffling for the accountants, whiteboards to manage the maintenance schedule. We have seen a transformation over the last 8 years where a lot of that work has been automated. Certainly it has become paperless; now we are really digitising.

I have also seen a shift in the skill sets required. The skill set has changed from practical, or process-driven, to analytical, information driven.

Our Customer Service Centre, for handling property maintenance work, also used to be a very administrative role. Taking complaint calls all day, and assigning the job to someone else to fix. But with the introduction of new technology, we have turned this area into a sought-after role for university students. How did we achieve that? We made it all about learning and exposure to the cool new systems.

We spent some time re-assessing what type of people we need to bring in to these roles, so that we can get the right aptitude as the industry becomes more and more tech focused. We are now targeting students from engineering degrees. We just hired an Environmental engineering student, who did a few subjects of data science. Perfect!

Data science is the fastest growing area of study

Big data has introduced a whole new industry of people– welcome to the Data Scientist, the Data Analyst, data visualisation, data miners, predictive analytics.

Data science is the fastest growing area of study. Courses have cropped up in most major universities.

You can study a Bachelor of Data Science at some unis, in the school of mathematics.

Studying this type of course might give you the data analysis skills, but they don't give you the context. If you want people who can bring meaning to the data, then hire people who have training and experience in property technology, so they can interpret the data and translate it into information, otherwise it’s just noise.

UTS and Sydney Uni both have a Master’s degree of data science and innovation. They promote it by saying that Creativity and innovation are integral components.

A Master’s degree takes a lot of work, a lot of time. A few of my colleagues have done a 3-day course at Monash Uni – “Data Science for Managers”. That sounds a lot more achievable.

The sky’s the limit

There are so many exciting new tools out there and we are seeing some good platforms that will do the analysis for you. The sky is the limit, as long as you know what you are looking for in the first place, and you have the right people in your team to get meaning from the information.

The journey of smart buildings and big data is a never ending story

The journey of smart buildings and big data is a never ending story. The more you get, the more insights you get from it, the more you will want. So don't design a project with a fixed list of deliverables.

Realise that in this space, you will be starting an evolving program where your people learn and grow and keep wanting more.

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