Smart Buildings: Four Principles for Turning Data into Value

A new perspective on People Analytics Data

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Our Smart Buildings collect enormous amounts of data every day.

But how do we turn data into value?

A surprisingly related field answered this question years ago.

Let me tell you how they did it, and how we can do it too.

Over the past decade, the field of Website Optimization has managed to add tremendous value to the business goals of various organizations. The intention of this blog series is to investigate whether we can transfer the value from the web to real estate through IoT. In doing so, we will explore a new approach to unlocking the value in People Analytics Data from Smart Buildings.

In the second part of this series, we will apply the taxonomy from the first article to translate Website Optimization theory to Smart Building Optimization theory, leading to four principles that will help us create a new value from our data:

Principle 1. Become conversion-centric.
Principle 2. Follow the conversion rate optimization steps.
Principle 3. Have a lean way of working.
Principle 4. Start simple, and follow the growth path.

A Recap of the First Article

In the first article of this series, I discussed the many similarities in structure between Smart Buildings and websites.

First, I explained how the rise of IoT enables us to precisely track the activities of the users of our buildings. Then, I showed that this tracking of user-activity is very similar to what software such as Google Analytics has already been doing for websites for many years.

The field of Website Optimization, of which tracking is an integral part, has proven to add huge value to the business goals of various organizations. The idea is, that if we can compare Smart Buildings to websites, and if we can track the activity of users in both these domains, then this could very well mean that the methods and value from the field of Website Optimization can be transferred to Smart Buildings.

Finally, the first article introduced a basic taxonomy that enables us to translate the methods and best practices from Website Optimization to Smart Buildings.

Our Next Step: Ask the Expert

After introducing the taxonomy in the first article, it was now time to put this tool to the test. I have done this by interviewing an expert in Website Optimization.

My interview was with Timo Stegeman who, as an Optimization Consultant, has had years of experience in successfully optimizing websites for global retail brands. Within his organization, Timo is responsible for overseeing the full optimization process for the websites of various customers. This makes Timo the perfect first candidate to share his expertise for successfully optimizing websites — and perhaps Smart Buildings.

During the interview I asked this expert to describe the process(es), methodologies and best practices that allow the field of Website Optimization to add value to a business.

After the interview, I tried to use the mentioned taxonomy to translate his website methods into a set of guiding principles for building optimization. A set that, as I hoped, would eventually form the foundation of Smart Building Optimization.

The outcomes of this first test are promising, and provide us with worthwhile directions for further research and the motivation to pursue these.

The Four Principles of Smart Building Optimization

The basics win fights.
—  Robbie Lawler

In the remainder of this article, I will outline a set of four guiding principles that I distilled from my interview with Timo. These four principles could form the basis for a theoretical framework that can be used to turn people analytics data from Smart Buildings into value for their business. In the forthcoming, third part of this series, I will apply this theoretical framework to a first practical case.

Principle 1. Become Conversion-Centric

From my meeting with Timo, I learned that Conversion Rate Optimization, or CRO, is a more accurate name for his field of expertise than Website Optimization. The reason for this is that the core of Website Optimization is all about achieving the highest rate of conversion on a website. But what does conversion rate mean?

Conversion Rate is the percentage of website users that take the action that the website owner wants them to take: buy a product, order a brochure, or make a reservation.

The conversion rate that a website owner is aiming for, should always be linked to the goals of his or her business. Through Conversion Rate Optimization, the website is then optimized so that its contribution to these business goals is as high as possible.

The idea of applying the concept of conversion to real estate is a very interesting one. It would enable building owners and managers to measure the degree to which their real estate contributes to their business goals — and to assess whether initiatives for building improvement actually move the needle where it matters. With the rapid development of IoT over the recent years, we are now able to track building user behaviour with ever-increasing accuracy in Smart Buildings. This development should also allow us to measure conversion with increasing accuracy as well.

It’s important to note here that the concept of conversion is not exclusive to sales-oriented real estate. Conversion can potentially be applied to many types of buildings; from offices to museums and from universities to airports. My goal is to construct and test a theoretical framework that can be used for optimizing all kinds of real estate.

Conversion: the Macro and the Micro

Following in the footsteps of the field of Website Optimization, Smart Building Optimization should also distinguish between two types of conversions: macro conversions and micro conversions.

A macro conversion is realized when a user has taken the final, most important action that a website owner wants the user to take along his or her user journey (visit). For a web shop, the macro conversion could be finalizing the process of purchasing a product. Translated to brick-and-mortar retail real estate, this macro conversion would be exactly the same: the purchasing of a product.

Micro conversions are the smaller desired actions that the user takes in order to finally arrive at the macro conversion. Examples of micro conversions for a web store are: signing up for a newsletter, clicking an item to inspect it further, putting the item into the shopping cart, and checking out. In a similar fashion, we could say that micro conversions for a physical clothing store are: browsing through the clothing, trying an item in the dressing room, and lining up for the cash register.

For both the web store and the retail store, optimizing these micro conversions can be highly beneficial, since improving the conversion rate for each of these micro conversions leads to an increased conversion of where it really matters: the macro conversion.

For brick-and-mortar retail stores, it is nothing new to measure the macro conversion. This is done fairly straightforward: if 1,000 people enter a store on a particular day, and 400 people buy at least one item, then the macro conversion is 40%.

Measuring the micro conversion within a retail store however, remains less, or even completely, unexplored. The most likely explanation for this is that it has been fairly difficult to measure a micro conversions. How would one measure what percentage of shoppers actually ends up at the cash register after trying on a piece of clothing in a dressing room?

Being able to collect this data however could be highly valuable. It would for example allow us to track whether modifications to a dressing room, such as installing mirrors that make the shopper look taller, increases the rate at which users proceed to the cash register and purchase the piece of clothing (the macro conversion).

The rise of IoT, combined with creativity, makes previously unmeasurable micro conversions now measurable.

Principle 2. Follow the Conversion Rate Optimization Steps

Order and simplification are the first steps toward the mastery of a subject.
— Thomas Mann

An important takeaway from my meeting with Timo was realizing the rise in the level of complexity and professionalism that has taken place in the field of Website Optimization over the past decade. In retrospect, I can say that my representation of the process of Website Optimization in my first article was a little too basic. In reality it is so much more than simply tracking user behaviour through Google Analytics and then changing the website for optimization purposes.

In Timo’s view, before any optimization is finally applied to the ‘live’ website, a complex and comprehensive testing process must take place. This testing process should include: conducting strategic analysis, developing hypotheses, designing experiments, conducting experiments, analysing data. All of this is realized with a high statistical precision, and using a wide range of tools.

In order to carry out this testing process, a whole team of experts from various disciplines should be assembled. For example, Timo’s team contains Website Analysts, User Experience Researchers, Website Designers, Experiment Managers, Program Managers, Quality Assurance Officers and Developers.

As a consequence of the methodological rigor and richness of expertise that these various fields and disciplines bring, the quality and validity of a developer team’s results can reach impressively high levels. Even if we could only start to translate a fraction of all the website practices to real estate ones, this would be of tremendous value. And that is exactly what we are attempting here.

The methodology of Website Optimization is based on three core concepts: Process, People and Technology. At this point, I will mainly focus on outlining the concept of Process. The main reason for this is that it is the logical first step: once the design of the Process has been completed, it will be clear from this design what People (specialists) and Technology (tools) will be required.

Below, I will provide a basic description of the five-step Website Optimization process, loosely translated into Smart Buildings Optimization language.

Conversion Rate Optimization in Five Steps

This five-step optimization process should enable any person to effectively optimize (conversion in) any type of building based on conversion theory.

Step 1. Set Goals

Your first step in the process is to set your optimization goal(s). Is it to increase revenue? Is it to boost user productivity? Or perhaps user well-being?

After setting these goals, you will look for factors that you can modify in order to achieve these goals. For example, if you want to increase the revenue of your physical clothing store (goal), then you could try to increase the number of people that buy an item (factor). This could perhaps be achieved through taking the following actions (modifications): attempting to change the store lay-out, tweaking the lightning, or enhancing the fitting room experience.

Outcome for this first step: a list of goals you want to achieve, and a list of factors that you can influence to achieve these goals.

In my upcoming article, I will introduce a tool that will help you identify which factors you can target for achieving the optimization goals you want to set.

Step 2. Formulate Hypotheses

The second step is to collect data and insights about your current performance on the factors you selected, and to learn what actions you can take to positively affect these factors (modifications). These data and insights can for example be found by looking into your current user journeys, analyzing user traffic, collecting building data, or conducting user surveys and interviews.

Outcome for this step: a set of hypotheses that can be tested. An example of a testable hypothesis is: ‘by using new mirrors in our fitting rooms, we will increase our conversion rate by 3% over the next month’.

Step 3. Design Experiments

After putting together a set of testable hypotheses, it is then time to design and plan experiments through which you can test these hypotheses. When designing these experiments, it is important to strive for experimental and statistical validity. In my opinion, this is the most challenging aspect of Smart Building Optimization, although it’s one that can be overcome. Again I refer you to my forthcoming article, in which I will design a real-life experiment following the four principles mentioned.

Outcome for this step: a list of designed experiments to test your hypotheses and experiment planning.

Step 4. Conduct Experiments

In the fourth step, you conduct your designed and planned experiments. During this step, you will focus on quality assurance for the experiments, monitoring (predetermined) metrics, analyzing outcomes, reporting outcomes, and sharing results.

Outcome for this step: having your experiments up and running, and having decided which modifications you will implement into your ‘live’ buildings after the experiments end.

Step 5. Implement Improvements

In the final step, you implement the changes that you experimented with that were successful. If your experiment was representative for multiple buildings across your portfolio (which I highly recommend you aim for in designed experiments), then you could choose to scale the changes across these buildings. Outcome for this step: having your building(s) further optimized in accordance with your business goals, supported by clearly quantified evidence.

In order to go through the process as effectively as possible, however, there are two more principles to be reckoned with. We will go into these two principles next.

Principle 3 . Have a Lean Way of Working

I want to get lean and mean, keep it minimalist.
— John Cale 

Another key takeaway from my meeting with Timo concerns the used method of operation.

Website Optimization is all about going through a cyclical process of formulating hypotheses, experimenting, validating and scaling in rapid succession. This method of working, with its shorter lead times, quicker insights, and faster adaptions to the website, results in a continuous flow of optimization initiatives.

This process will sound familiar to entrepreneurs and innovators, since this process has many similarities with the fields of Lean Startup and Design Thinking. The use of concepts that underline this similarity even more are: personas, customer journeys, the value proposition canvas and the build-measure-learn cycle*.

The potentially more capital-heavy field of Smart Building Optimization could benefit enormously from the same modus operandi, because working lean will produce lasting results fast, in a highly efficient way.

*In the final description of Smart Building Optimization, many of the mentioned field-specific concepts will be described in a language that will be understood by a wider audience.

Principle 4. Start Simple, and Follow the Growth Path

If you’re walking down the right path and you’re willing to keep walking, eventually you’ll make progress.
— Barack Obama

When Website Optimization started, its methods were limited in number and complexity: website owners were able to track and measure only a fraction of what they can today. Data was not used as effectively as it is today, nor were the teams involved as rich and diverse as they are now.

At this moment in time, as stated earlier, the field of Website Optimization is comprehensive.  The vast range of possibilities and the level of complexity of Website Optimization may at first seem daunting to a first-time user.

My initial thoughts after my meeting with Timo were: where do I even begin with translating the methods from the web to real estate? What do I measure first? Which experts do I involve?”

In our case, it is important to remember that it is always a good idea to start relatively simple. After that, you may realize that this comprehensiveness is in fact great news: a bigger set of Website Optimization methods will undoubtedly bring with it more opportunity for developing a similarly big number of methods and tools for Smart Building Optimization.

In the future, I can imagine a rich, multi-disciplined team working on Smart Building Optimization. These teams could include construction engineers, architects, behavioural psychologists, designers, technology experts, data scientists — and of course, website optimizers.

Lessons So Far

We’re still in the early days of Smart Building Optimization. But I believe that the principles presented in this article are essential building blocks of a very promising methodology. Our proposed methodology is ready to be tested and is ready to prove its capabilities in unlocking new value from people analytics data. In doing so, we should keep the key takeaways from this article in consideration:

  1. In this second article, we applied the taxonomy from the first article to translate Website Optimization theory to Smart Building Optimization theory.
  2. We now have four principles at our disposal that offer a step-by-step plan for professionals looking to create new value from people analytics data.
  3. We expect to see that this methodology can be applied to most of the datasets that we already work with. We will just be looking at our data from a different perspective.
  4. We are likely to come across gaps in our current way of collecting data that need to be closed before conversion can be adequately measured. This could lead us to collect data in ways that we perhaps otherwise would have never thought of.
  5. Further investigation into the history and development of Website Optimization will be needed to be able to identify the field’s various key development points. By doing so, we hope to avoid unnecessary mistakes and speed up development. For this reason I have planned an interview with the founder of Timo’s Website Optimization agency — who was part of the Website Optimization field from the very beginning and played an important part in its development.

Our Next Steps

As indicated, I will continue to build upon the Smart Buildings Optimization theory by interviewing experts from the Website Optimization field. In part three of this series, I aim to identify the basic starting point for our new field, and to formulate a growth path from there on. Think of this as a Smart Buildings Optimization maturity model.

In addition to this series of articles, I will from time to time publish articles illustrating the theory by designing and describing real-life experiments (for example, A/B tests in physical stores and offices). To me, this is where the real fun begins. So, my next article will be one of these appliedarticles.

In the meantime, I invite you to get in touch and to share your perspectives, ideas and opinions about Smart Buildings Optimization. If you would like to experiment with (parts of) the theory presented, and want to apply a conversion perspective to your people analytics data – I’d be happy to think along. The more experiments we can get up and running, the more insights we can get into the potential value that lies in this methodology.

One Last Thing

Thank you very much for your time and interest. If you enjoyed reading this article and found it to be of value, please share it with your friends, and stay tuned for the upcoming articles.

Happy optimizing.

Special thanks to Timo Stegeman for sharing his expertise in Website CRO.