Using a Guide to Pass Through the Analytics Wilderness Safely

Let’s face it, “Analytics” is a confusing term. Whenever I try to tell people what I do, they get confused. To simplify this, I like to use the analogy of cutting a trail through the wilderness. “Analytics”, after all, is more about the questions you ask than the data itself. So, let’s talk about what works

Every wilderness adventure needs a good guide, and that's exactly what an analytics partner is: a translator and guide.  One who seeks to understand what the nature of the business problem is first, before jumping to what the technical solution could be.

A good partner is one that sits in the middle ground of business and technology. They get and understand technology, and can develop solutions themselves if the tools are put in front of them. However, they approach problems, not by telling other people what to do, but instead, listening to the problem to help create the most effective approach. 

There are all kinds of "analytics" techniques, and they all involve navigating a new path with data. It’s easy to get lost in the different definitions to gather, organize, and analyze data because the methods are vast: from machine learning, statistical analysis, data transformation, to data visualization. Analytics is a blanket term that includes all these things; so, when people ask me “what is analytics”, they often cite one of these ways and say, “is that what you mean?” 

Yes, but not really.

Effective questions

An “analytics partner” is not someone you hire just for their technical expertise. The ability to do the job with precision and accuracy is a baseline expectation. You hire them because of the way they pose effective questions, which save you from going down the wrong trails.

Many times, consultants will suggest that you build a freeway through your data wilderness, or put an expensive solution in place that doesn’t really play well with your environment or culture. You don’t want to build a house in a location that doesn’t make sense.

Rapid approach

“Design Thinking” is a term that better describes good analytics than does much of the analytics terminology because the active verbs in the process are similar: “Empathize”, “Ideate” and “Prototype”. Whereas analytics speaks in more conceptual techniques which sound complicated and mysterious...confusing. In an attempt to sound impressive, it alienates non-experts from understanding it.

For example, in the Design Thinking process, "Ideation" and "Prototyping" are key steps to help create a workable solution quickly.  The first idea is rarely the best one, so by testing and re-building it a few times, it's more likely to produce results that move an organization forward.  This is different than the traditional IT approach to solutioning, where precise “requirements” are needed first to build a more static solution. This is often at the heart of why solutions take so long to build but often miss the mark of what’s really needed.

Travel light

Analytics partners are hired because business owners don’t have the resources on their team, or their team is fully committed on other things. The last thing they want is to have a partner come in and require their folks work 25% harder. They need a partner who has the experience to understand the right upfront questions – what are you trying to accomplish? Where is your data? What is the quality of your data? – and then is gone. Not burdening at every step or bogging down because things aren’t clearly defined.

When all this comes together, the experience with an analytics partner can be transformative. More than just a technical solution provider, because they serve as a translator and guide to carve a beautiful, new path through the data wilderness for you. They don’t seek to tame the forest or build a highway through it, because the right next solution may not be in the part of the forest you think.

Passion: The Job To Be Done

Jobs to Be Done

One of my clients first introduced me to Jobs To Be Done theory, and since then, we have used it as one of the tools to help uncover consumer needs states in certain situations, in order to better understand “white space gaps and opportunities.” 

What I appreciate about this theory is that it starts from a place of “need or desire” rather than a place of “what’s missing” or lack? Many traditional methods for understanding wants and needs is looks at filling the gap to produce products - starting from a place of what's missing. People can typically comment or think about how to do something better than what it is.  When starting from a place of lack, one cannot help but stay in a place of lack. 

But when one starts from a place of desire, suddenly everything shifts. Let me give you an example, For years I've been trying to figure out how to change things in my company that are frustrating to me – the feeling of never having enough time, wearing too many hats,wanting to create new ideas or better systems but feeling buried in the work we currently have.  From that mindset, I've been evaluating what's missing, what's not quite right, what I would do different as a starting place for trying to solve the problem.  And I haven’t gotten very far.

A Trip to Austin

So, I took a few days just to myself, thanks to my wonderful husband (who I think was secretly ecstatic for a few days alone and my mom, who took my daughter for a “cousin camp”).  I went down to Lake Austin Spa to spend time with… me.  I did this thinking I would come back with a new purpose, life planned out, with dramatic shifts along with a strategy.  Instead, I came back with something different.

This may have been the only few days I’ve lived without an agenda as an adult.

I took a step back and I slept, walked, read and journaled.  And then on my 2nd day, I started flipping through magazines, pulled out every image that attracted me, or emotionally drawn to, then labeled, and created a collage .  Suddenly, I was in research mode, and knew what to do – this time I was researching myself!  I started looking and what resulted was a really specific “Job to be Done.”

Turning it on Myself

I decided to start from a place of desire. I started asking myself why do I feel the urge to change? why is finding my passion so important to me? I have a great family and I'm doing work that I love and feels interesting to me so what's missing? I also asked myself the question what do I most love? 

Looking at my collage, I realized I needed to develop some patterns or themes. So, my second step was to create definition around the pictures, looking for similarities and differences. When I finished, I had discovered that a lot of what I had passion for was already in my life! In the discovery of trying to find my passion I found that I already had it. What a concept!

Here’s how I translated my “vision collage” into a Job to Be Done.  I’ve wanted to buy or design a “creative, innovation space” for awhile but I have been rejecting in my mind that it’s a viable option…due to all of the negative self-talk rattling around in my mind.  But this process allowed me to open up to the “why” of how this is important to me,...here’s how I organized the picture and post-it data using the JBTD theory.

·      Note: the sentence structure we use for our research, I slightly changed.  Instead of “I use”, I replaced with “I need”

I need (what)

-       to create a beautiful space where light, water, nature and creativity connect

-       an innovative, transformative space for me and others to create

-       space to breathe - to feel, to be, to love, to give thanks

When (the situation)

-       I’m in my current state of desiring a life that’s true for me

I want to (what motivates me)

-       create vibrant ways for people to come together for fun, cozy connection

-       help others find their joy and facilitate groups growing together

So I can (the outcome I want)

-       set myself free and surrender to loving what's important to me

-       explore into the unknown with a spirit of adventure

-       let go of what doesn’t serve me

In the end, what came up for me was unexpected. What I discovered is that I was not spending enough time implementing experiences into my life which gives me joy. So suddenly these themes that emerged allowed me to start taking action on some small steps and over the hump of feeling like I had to make some huge life change in order to find my passion or make things better. And in turn, it has brought newfound passion for fulfilling this dream!

Being Present Through A Lens

When folks say “follow your passion”, what often comes to mind are big ideas. Major dreams, many times ones we believe are unattainable. Things like starting a business, writing a book, or climbing an 8,000-meter peak. But sometimes following your passion is a series of small things, an activity that you find a way to weave into your typical day. Even if we struggle between passion and exhaustion in the job we choose, we can inject passion by taking small moments to do things we enjoy just for the sake of doing them. And in that doing, unpredicted benefits arise. For me, that’s photography. 

Like a lot of people my age who invest in photography, my interest started with back in high school where I learned to shoot black and white film on a manual camera. I enjoyed that tremendously, but It’s come and gone over the years without really sticking. I wasn’t willing to dedicate the time and money I felt was needed. Digital came on, but I wasn’t excited about the quality or expense – why spend a lot of money on a tool that may be out of date within two years, when you’re not even doing it that often to begin with?

Over the years my life became more complex. Having a child, juggling two careers (1 helping my wife’s business + a corporate gig), which has now have morphed into one, making room for family, friends, two dogs and a Shasta trailer. In keeping up with all that, there became less and less time to pursue hobbies. About four years ago, I acquired two items that used to be passions of mine as a teenager – an electric guitar and a digital camera. That guitar has not seen much action, but the camera took off. It was something I could carry with me to the events of my life, and was especially encouraged if I was aiming at my now 6-year-old daughter. Perfect!

Noble winner, Daniel Kahneman has said there are 20,000 moments in every day. They are all different and your brain remembers them them in slices. When we recall a favorite moment in the past, we are often brought back to one of these slices that were especially meaningful to us. This is where our brain recorded that moment as the one that captured the feeling best.

Photography trains you to be better aware of those moments. My daughter likes to take photographs now, too, on her waterproof/shockproof camera. This of course makes me very proud. Although she always likes looking at the pictures I’ve taken of her, she sometimes gets annoyed when I point the lens at her. To help her accept it, I told her that I am “collecting butterflies”. She asked me what that meant so I said, “memories are like butterflies that come in and then flutter away. I am trying to catch the pretty ones in my net so I can look at them later”.

Have I followed my passion by becoming a National Geographic photographer for a living? Not so much.

Have I followed it by weaving photography into the life I already have, and adding a layer of joy and appreciation to it? Yes, definitely.

What is that thing that you love to do for the sake of doing, that could maybe find a way back into your routine? You may be surprised by what it brings.

How to Build Data That's Useful

Analytics and Stroller Pushing

One of the best analytical lessons I ever learned was nowhere near my computer. My wife and I were gearing up to have our first child. We were shopping for a baby stroller. If you have done this, you know the choices are paralyzing. There are at least 20 options that are rated on multiple qualities. After hours of debating what should have been painless choice, we stopped ourselves and asked, “what is the most important feature here”. After thinking about it, my wife said, “I want to be able to reach down with one hand (because the other will be holding the baby) and pick it up so it collapses, then toss it in the back of the RAV4 in one motion.” Suddenly, 20 options went down to 2 or 3, and we made a decision a minute after that.

Good data insight development follows this approach. It is not an attempt to build the Encyclopedia Britannica, it’s an agreement on what piece of currently unavailable information would make the most difference to the people who actually run the business. Here is a fun little video of me talking about this.

Back in 2011 I took a leap of faith. I left the stability of Pepsico to lead an analytics group in a much smaller Energy company. At that time, I was introduced to a new software called Tableau. It seemed pretty cool, and was easy to learn if you were a strong excel user. So off I went with my team to build reports from the database of company information we had put together.

One of the first and certainly most notorious reports we developed was for a “very eager” and attention-challenged marketing manager. The good news is that he loved data and believed in not making decisions without it. The bad news is that there was no end to the data that he felt he needed to look at.

My team went on to develop the report exactly the way that he wanted it, with all the different possible views and filters he could think of.  With this one report, he would be able to see everything, and answer every question that his directors could pose.

This is an example of what it looked like. My team gave it a name: “Filters Gone Wild.” No one else in the company could stand to use this report for more than two minutes without needing a glass of scotch.

So why to people do this? Isn’t it a noble intention, after all, to want to see more data? The reason is because complexity creates its own burden, As it turns out, consuming data is a lot like purchasing jam - more isn’t always better.  Not only is there a point of diminishing returns in how satisfied we are, but our ability to act is reduced significantly as well.

That was a really interesting role for me, and I’m glad I took it. Not only did I learn a lot of new, useful skills, but more importantly I got to see the gamut of “clients” and how they wanted data. The better ones understood this concept of simplification.

Around the same time, there was an article released by MIT, which put some science to what I was learning. They surveyed a few thousand people at multiple companies and determined that top performers were five times more likely to use analytics than lower performers. No surprise there, but what was more interesting was how the top companies approached data.  It wasn’t about budgets or sophistication of software; the lower performers cited development process and managerial issues as a major contributor to blocking progress. What - people are getting in the way?!?

A recent client experience motivated me to write this blog. The team had purchased all the software it needed to bang out good reporting. They had a small army of internal folks and contractors who could wrangle and structure the data as good as anyone. But when the six-month check-in time on a nine-month project came, they discovered that only rudimentary reporting had been developed, and that the internal clients were disappointed to the point of considering pulling the funding for the expensive software they purchased.

Why? Because the IT developers who were in charge of it had treated it as a requirements fulfillment exercise.

One of the key points of the MIT article was a concept they called “start in the middle”. In their findings, they saw a trend in the approach of effective teams where they would simplify the issue to discover the most relevant information to move the needle the most, and then iterate against that until they honed it to a useful state.

It’s a conversation between business people, that happens to use technology as a tool to make it come to life. There is no requirement to gather, because it’s never really known completely what is needed until the discovery begins. It’s not a conversation with executives, it’s with the frontline managers and directors who make the business happen. Once they start becoming successful, peers start taking notice and the path to a data-driven culture organically grows.

Do You Need a Data Scientist?

Data Science is all the rage. Career interest has surged, programs are offered at more and more universities, and every company is talking about needing it. But do you? How do you know, and when would you hire one? These are questions that get glossed over in the race to be smarter.

Data Science is a powerful tool  - it can unlock understanding in data, which leads to new insights no one considered. However, often the most practical insights arrive as a result of Data Mining and posing the right questions.

At the latest MSMR conference at UT Arlington, the keynote presentation “Behind the Corporate Curtain” by Simon Chadwick talked about where corporate research spending was headed in the next five years. The top two items of incremental focus, above CX and Digital, was Data Analytics and Data Mining, plus integrating multiple data streams.

First, let me break down what is meant by these three “Data” terms we’ve mentioned – Analytics, Mining, and Science:

1. Data Analytics – working with the business to describe, predict and improve business performance through data. Broad subject that includes many tools and techniques.
2. Data Mining – examining large data sets to generate new information or insights. A tool of analytics used to dig in, clean up, and see what nuggets there are in the data.
3. Data Science – applying statistical methods to data to generate new information or insights. A tool of analytics used to apply a specific technique to generate a specific result.

Remember that finding that got Target all the press a few years back, where they could predict when a girl was pregnant before her father knew? That was heralded as a slick data science discovery, but it wasn’t, it was just good ‘ole fashioned data mining. Finding that right pebble on the beach.

Target had conducted a study to understand what major life events force a break in normal shopping routines, opportunities to capture new customers. One of the more interesting ones was getting pregnant. Around the same time, they were pulling all their shopper and sales data into one spot to allow them to track purchases by customer.

Then, someone asked the following: “what products does someone, who we eventually realize is pregnant, purchase in the early stages of pregnancy?” If Target could get them in the door early, they would likely stick with the store for all their later needs. After just identifying those customers and walking backwards through their shopping data to look for patterns, the answer was not baby gear, it was  unscented lotions.

A client that I was working with told me recently, “I can bring in a statistician, but I think I’d also have to hire someone to accompany them to talk to the business user. They know the mechanics, but wouldn’t be able have a meaningful segmentation discussion.” These are wise words from a leader who is trying to bring advanced capability to an organization. A more inexperienced leader would hire a small army of statisticians and hope the “build it and they will come” strategy pays off. It typically doesn’t.

Capital One is a company that jumps to mind often as a leader in data science. They employ an army of statisticians, and consider how they analyze data to be a completive advantage. There is a famous Harvard Business School case study on them that explains this, but also more importantly, describes a business process that they followed early on, which allowed them to gain share quickly before their competition could react: testing and innovation. 

They were relentless in conducting market testing for different offers and products, targeted to groups of people that they thought might respond.  Yes, there was data science behind the segmentation and prediction that helped shape the hypothesis, but the sheer volume of testing, measuring and validating was what set them apart. They were throwing a hundred pieces of spaghetti on the wall and seeing which 5 would stick, then aggressively going after those ideas before their competition could react. They used data science as a methodology, but their business model described in that moment of their history was to outsprint, not outsmart.

The statistical analysis of Data Science is a powerful tool, and well deserves its place in the toolbox of any company doing advanced analytics. But advanced comes after intermediate, and when an intermediate company tries to follow a “me-too” advanced strategy, it is ignoring the value of what intermediate data mining can bring. All too often this wastes valuable time for a company, trying to be something they aren’t…yet. Data science is part of a mature progression of data capability, formed from having as a clear sense of how it can successfully integrate into a business process before the first study is conducted.

Road Stories on how Married Couples go into Business Together Lesson #3

Working for my wife has its challenges. In my last blog I talked about how it’s particularly fun when you quickly discover that your new role involves knowing the subtleties of what and how your wife likes her coffee. You will be getting a lot of that for her until you figure out how to bring in some bacon.

What’s positive about being married and working together is the flexibility. Although things get crazy at times and the ride is much less predictable, there is more flexibility in scheduling time off. Gone are the days when I had to disappoint her with the response that I can’t take an opportunistic four-day weekend, because I’ve used my corporate accrual allotment of vacation year-to-date. Like a lot of corporate terms, it’s hard to know what that means exactly but it’s safe to say that you’re screwed.   

I’m learning to be more grateful for the times that we can sneak away.

So, in this post I wanted to simply make that point, and share some photos I took of our trip we took to Cancun for her “birthday week”. Thank you, Marriott reward points!

Enjoy!

Boy that water is a pretty blue.

And the sunsets are stunning above the sea

April was pretty darn relaxed

And able to spend quality time with Autumn

My daughter thinks she is Moana

And did her happy dance every day of the trip

April’s perspective:

When can I go back?

How to Love Spring Cleaning

It’s that time of year again. There’s something primitive in the sense we get come springtime. Maybe we’re just wired this way. Spring brings with it a desire to clean house, to get rid of the stuff. The stuff that has magically survived the selection process and found what seems to be a permanent home in our garage, closet or pantry. We used it before, a long time ago, and it would really come in handy if that time ever came again. Yet it hasn’t, so it just sits and waits another day.

Here at ABRG, there are two things that describe us well: we love research, and we love learning about how to be more efficient (try running a thriving boutique research firm with four people and you’ll understand why). Recently, we had the opportunity to do both. While in an ideation workshop with a client, we conducted a practice brainstorming exercise on the topic of spring cleaning. To get people geared up and in the mode of ideation, we typically have them practice on an off-topic, non-business subject that’s ripe for multiple ideas.

The topic of spring cleaning fits well, so we asked them to come up with as many ideas they could on “what’s a creative way you could attack a spring cleaning exercise”? To set the stage we give them some guidance on how to keep coming up with ideas:

1. Land on something, and think of other solutions
2. Wish list it – what could I do if….
3. If you feel that you can’t relate, think of who you could ask
4. Work individually first, then as a group
5. When you’re stuck, move around or talk to someone

The answers were creative, practical, and fun!

A good ideation generates multiple ideas without judging them on whether they are good or bad, because sometimes the crazy ideas lead to break-throughs of innovation.

• Live in a hotel.
• Open a bottle of wine.
• Make the kids do it.
• Buy stock in cleaning companies.
• Ask Alexa.

Some responses had themes of minimalism, which ironically asserts that happiness is achieved in life by having less, not more. The less stuff we fill our space and lives with, the more we are open to things that really matter – time with family, focused effort on our passions, appreciation of our surroundings. One blog we follow at ABRG is Becoming Minimalist. If you follow the thread of minimalism you’ll recognize these suggestions to overcome decluttering:

1. If you haven’t used it in three months/one year, throw it out.
2. Does it bring you joy?
3. Don’t start reminiscing.
4. Would it be that hard to replace?
5. Have I worn it in 2 months?

Some ideas had efficiency in mind, how to get through the emotionally tough nature of the process in a way that works. At ABRG, we follow Asian Efficiency and have gotten a ton of great advice through their resources over the past few years. There were some good ideas on how to best go about it:

• Go room by room.
• Clean as you go.
• Hire people and give them each a room.
• Go through the out-of-site, out-of-mind places.
• Make someone else go through your stuff and throw out anything that doesn’t look good.
• Buy storage bins with labels – prioritize what you store, and once the bin is full throw out the rest.

This year, we’re going to make this painful process more fun and efficient by tossing in a few of these ideas. We hope you pick up a few tips that help you, too!

Art of Data Simplicity

I recently made the leap from the corporate side. After 15 years of helping people understand and solve problems with their data, I decided that my profession would be more enjoyable as a consultant, where I would be able to see a wider variety of challenging work. That’s certainly been the case!

Like a lot of people, I’m amazed at how the data world has grown. The amount of data and the tools available are impressive. I wish that I had some of these tools available to me when I started my journey, but then again, I wonder how much of that would have mattered. Like a photographer who gets better through the process of just shooting more pictures, a data person gets better by just analyzing data – whether it’s on a spreadsheet or a sophisticated analytical platform.

Which brings to another theme I’ve seen in my 15 years, and has recently gotten worse: people forget the power of simple data. It’s a syndrome that’s common and has blown up with the increase in data and tools. Many organizations rush to gather as much as they can and purchase tools to understand it - afraid they will not be competitive without it.  What’s more likely than not, though, is that they wind up with mismatched pieces or tools that don’t play well with each other.

I’m reminded of the book Data Smart, that walks the reader through the basics of data science through follow-along exercises in Excel. By doing that, you understand the data at it’s lowest level, and get what the statistical method is doing far better than if you had used a sophisticated drag-and-drop software. Great read.

Another great read on that topic is Data Science for Business, which does an excellent job of explaining the “so what” and “why does it matter” behind different statistical methodologies. What you method you choose to follow shapes whether or not you’re going to get a result that means anything.

In thinking back on it, my whole data career has been around getting people past this, creating things that are simple and actionable and move them forward quickly. It’s not just a technical exercise. Like qualitative marketing research, the approach that’s used makes all the difference. “Garbage in, garbage out” is often what got people to that place to start with, so empathizing and getting to the right question is a necessary first step.

Take customer experience for example. There are a lot of great tools out there, from Qualtrics to Medallia, and more and more companies have staff dedicated to CX. However, what most of them can’t answer is “what effect will this campaign have’, or “what is the value of converting a passive to a promoter’? They are not getting at the “so what” behind the data, because they are relying on the system-fed metrics that their platform provides.

Getting past that involves the right mix of business and technical know-how. One without the other produces limited results. 

Would you like to know more about what ABRG can do to help? Read this paper on our capabilities and case studies.

Road Stories on how Married Couples go into Business Together Lesson #2

When I was in my corporate job, April and I had always joked about how dangerous working together would be. We enjoyed talking about the similarities between our jobs, particularly in how we were both helping people understand what makes their customers and business tick, but also felt good about being able to go back to our own worlds the next day. Partners, but masters of our own spheres.

Then working together finally started to make too much sense to ignore. I had already made the transition out of a corporate role and to the consultant side, and why have two competing consulting careers when you can join forces and make it even greater?

I read the blogs out there and listened to other couples that worked together. It was good to know I was not alone – here are a couple of articles that talk about this condition, which could be listed in the DSM-5.

I’m going with this advice, though:  “Get used to the fact that whoever is joining the other person’s company is initially lower on the totem pole. However, once you get to the other side it’s better than what you were doing before and you would never go back. Once you find your stride and each has their own role and authority, it’s great!”

What they don’t tell you as much is what it’s like for a man to go to work for his wife. I now believe this is God’s sense of humor as payback to men for not having to bear children.  

I responded to a question from my wife-boss the other night. Right after I joined the company, her logistics expert was scheduled to go on a three-week absence to the Philippines. So guess who needed to learn her role pronto, to patch us through an upcoming project, which fell during that timeframe. After another long day of absorbing a massive amount of details and then getting bombarded with ten more items on my to-do list (that I really don’t know when will get done, but they are captured, by golly), I was less than passionate and a bit numb.

She asked, “are you feeling resentful about something?” I said, “no, I just feel a little emasculated, is all.”

All those ideas of grandeur about my involvement in the business had been reduced to a reality of me being her administrative support. Can I get you some coffee? Yes, all your research materials will be printed out and put in piles and be ready for you. Yes, I will ensure that there is a bag of markers and post-its with at least four different colors of each in your car tomorrow morning. These are all important tasks, don’t get me wrong. April’s clients are spoiled by the level of detail that she brings to projects. It’s just that they weren’t what I had in mind when I signed on…

There are great things in store for us, and I know it will evolve into separate management roles to do these new and exciting things. The transition period, though, is a bitch.

April’s perspective: Trust me - there’s nothing I want more than for Lloyd to start leading the business! But… we have competing priorities: he has to learn how we do the business, AND yes, we have to strategically craft the right role for him, but most importantly, we have stuff to get done! What better way to learn than by doing? Get on it, stop complaining, we have a business to run!

Lesson #2: Bring an apron, guys, if you want to join your wife’s business. Hide your man card in a safe spot in the garage.