Chapter One of Transformative Intelligence Why Bad Business Intelligence Matters

So. Many. Clients. I have worked with countless businesses over the years. Healthcare organizations. Nonprofits. Manufacturers. Entertainment multinational conglomerates. Giant freaking technology companies and tiny little insurance sales companies. I’ve worked with businesses in every income category, across the profit to not-for-profit spectrum. I’ve worked with drug manufacturers trying to cure diseases and defense manufacturers improving our war-making capabilities.

No one has seen it all. But I’ve seen lots. Maybe more than my share.?

And with a few notable exceptions, I feel pretty safe making the following statement.?

Most businesses are TERRIBLE at Business Intelligence and analytics.?

I have dedicated a whole chapter to these sins. When I was young and arrogant (as opposed to a bit older and a bit less arrogant), I thought “what the heck is wrong with these organizations? Why can’t they figure this stuff out?!”?

American businesses, no matter the size, are rarely set up to have open minds. In Buddhism, Shoshin, or Beginners Mind, is “an attitude of openness, eagerness, and lack of preconceptions when studying a subject, even when studying at an advanced level, just as a beginner would.” (Wikipedia)?

Many businesses are not set up to allow individuals to learn. The design of organizations can feel diametrically opposed to meaningfully benefitting from real BI and analytics.

Why is this? The whole topic could be a different book. But as an overview, think about the following...

I once did market research for a client and found that their product met several needs that virtually NO RESPONDENTS identified with having. We got data from a representative sample of organizations and very few of them ‘got it’, let alone needed it. The company for whom I was doing the research sold other products. They had the opportunity to use the research to rethink how they positioned this new technology. But what did they do instead? They got mad at us! They blamed the research rather than learning from it.

This company saw results that contradicted their assumptions as dubious. They had a chance to learn something and opted instead to ignore the results. They invested money in a product and did not like that it met needs no one seemed to have. Rather than using the findings to keep learning, they ignored them.

Beginners Mind

This book is all about enabling Transformative Intelligence in organizations. I approach this from three perspectives - Business Intelligence and Analytics, Digital Transformation, and Organizational Learning. But before I go too far down that road, I want to explore why Beginners Mind is crucial.

Once while volunteering, I equated something in an addiction research program to a koan, or repeated phrase in Buddhism, and the director of the program told me he was a religious man and did not go for such things! That was many years ago and since then I think people have gained comfort in looking across the world for things that can teach us, so long as we keep an open mind (and don’t steal the cultures of others).

This IS the very definition of Beginners Mind. In short, business needs to constantly approach learning as though new to a task. It feels safe to say that one of the most dangerous phrases in business is, “we do it that way because that is the way we’ve always done it.”?

As much as corporate-speak praises ‘thinking outside the box,’ this is rarely practiced. When it comes to actually doing things differently, people often struggle with knowing how. The truth is, just randomly doing things in a new way willy nilly is far more dangerous than doing things in a way that is tried and tested.

Beginners Mind is the first step in Business Intelligence and Analytics. In turn, Business Intelligence and Analytics is the primary driver of Transformative Intelligence.

At the heart of it, inquiry and the willingness to allow others to inquire should be at the forefront of Business Intelligence and Organizational Learning.

However, business pretty much exists in direct opposition to Beginners Mind. We take our policies and our processes and we calcify them into rigid procedures. Changing a policy or procedure is not a common occurrence at most companies. And it is often done in response to a problem, often by a very narrowly defined team of specialists.

In many organizations, corporate trainings often serve to disseminate rigidly defined information. People are onboarded into specific corporate ways. We conduct highly regimented regulatory trainings such as Data Security, Sarbanes Oxley, or OSHA. ?

All good and necessary things! I would not pretend otherwise. But none of these typically foster a culture of creativity, growth, or change. And in all these examples, the focus is on finding out how things are supposed to be done and then either training others to do the same or establishing experts to transmit this expertise.

Bastions of Beginners Mind

When organizations do show Beginners Mind, they are often limited to small pockets. The best example of when this is allowed to happen? Internship programs!

The class of 2019 Internship program at Microsoft released an amazing music video to highlight their time in this esteemed program. Another company had their interns create a training video that used the same fast cuts and quick jokes many college students could identify with from their time on social media. At a former company of mine, we were constantly having Interns offer new ways to solve old problems. Because of the freedom given to college students, they were essentially free to explore and fail. As a result, they were able to come up with some fascinating solutions to problems that were adopted company-wide.?

Did the interns also come up with stinkers? Oh yea. They often missed more than they hit. But they were doing new things and there was every expectation that failure was an inevitable part of learning.

Why do we give that up? Why do we abandon our Beginner’s Mind when it is the very thing we NEED in order to improve our organizations?

If I had to summarize this, I’d say that the problem is a failure of business systems to convert Business Intelligence into Organizational Learning.?

That almost sounds like a thesis statement.?In a radically over simplified way, I am hoping to take the process of learning and growing for organizations and move it into the domain of data and analytics. If I were to diagram Beginners Mind, this would look like the following:

In other words, when we have a new experience and we combine it with a willingness to learn and we apply past experiences without bias, we get Beginners Mind.?

But corporations don’t have a single mind. As such, the limits of this metaphor are obvious. We can’t expect everyone in a corporation or organization to have the same mind set.?

Rather, we need to create the circumstances for this type of approach. This book tackles this problem directly by asking what Beginners Mind looks like in an organization. I am suggesting it looks something like this:

Once an organization has gone through a Transformative Intelligence process, they can apply BI and Analytics to enable Organizational Learning.?

We Have to Move So Darned Fast

We manage sales by the month and quarter. What is closing this quarter? What closed last month? What is coming two quarter’s out? We treat marketing the same. Our time horizon in business is immediate. We use the past for some learning but mostly just let it go like so much water under the bridge. We typically look to the future in a couple of ways:

Specific predictions such as sales forecasts and production forecasts.

Broad, crystal-ball predictions (“Six Trends that Will Change Your Industry Forever” kind of stuff.)

But in all things, the need for immediacy and speed is paramount. Most businesses can’t stop long enough to process, learn, make mistakes, etc.

Real Business Intelligence and analytics are initially very inefficient!?

That is worth repeating - real Business Intelligence and analytics are initially VERY INEFFICIENT!

There is no way to overstate this. Even the most experienced analyst or data scientist should actually be cautious if things go too smoothly. They might be falling into the trap of not having beginner’s mind for a topic.?

Anytime organizations introduce new data and start doing new analyses, things take longer. And if businesses are truly ready to embrace Organizational Learning - this is a slow process of discovery. Before Edison patented what would eventually be thought of as the light bulb, inventors like Joseph Swan, Warren de la Rue, Alessandro Volta, and others were laying the scientific foundation and causing lots of accidental fires and explosions as they slowly moved human knowledge to the point of a lightbulb in every home.

I know that some (many) in organizations feel they are not inventing the light bulb! They are submitting invoices to get paid by clients. They are raising funds for a new playground. They are trying to find a marketing messages that increases click through.?But in all these cases, the use of digitally transformed processes and Business Intelligence will enable organizations to do things better, faster, and more efficiently. So yes, the initial process of BI and Analytics might feel slow and inefficient. But the outcomes are vastly improved operations, processes, sales, marketing, etc.

Every Christmas here in Rochester, NY, we have a concert called A Rochester Tuba Christmas. I think it used to be called Merry Tubamas, or perhaps that is just what I wish it were called. But the scene is magnificent. Hundreds of tuba players (and euphonium players - never forget them) of all skill levels, up on stage, blasting out the Christmas classics in all their tuba glory!?

I think it is safe to say that people played tuba well before Merry Tubamas came to town. And when the principle tuba-ist for the Rochester Philharmonic stands next to the 5th grader who just started playing tuba, they are probably going to sound different, play at different skill levels, and ultimately return different results. But when heard together, it sounds like a magical tuba extravaganza!

Some organizations represent the professional. Some represent the beginner. Some have already discovered what works and what does not in terms of Business Intelligence. Some are at the start of this journey. At some point, every organization has picked up that tuba the first time. Every organization should continue doing the hard work of learning to play it.

And to keep this remarkable metaphor going, most organizations actually feel like they already play the tuba but they are usually doing so with really bad habits, with terrible posture and position. Sometimes it is necessary to unlearn old, bad habits before learning to do things the right way.

And one last comment - never forget that the professional players carry forward all of their experience, all their years of tuba-awesomeness to learning and playing. Beginners Mind does NOT mean starting from scratch each time. It does mean leaving behind preconceived notions. It means being open to new ways.?

?It means doing whatever it takes to never say, “I will do it the way that I have always done it.” But rather, “how can I explore and learn new ways of seeing and playing.” This is what I want for organizations that want to embrace Transformative Intelligence.

For the rest of this book, my assumption is that everyone is learning the tuba! Learning to transform their organizations through BI is like learning a new instrument. And together with others in the organization, the potential for real, impactful change is huge when the process of learning is allowed to take place. Now go play that tuba!

The Oversimplification Paradox?

The Oversimplification Paradox states that the simpler something seems, the harder it is to do well. I think BI and Analytics suffers from this in many organizations.

In a sense, the Oversimplification Paradox is the result of a combination of assumptions. The first is that reporting is easy to do. It’s simple! It’s a low-level task for interns, for junior resources, or for solo-resources. The perspective that it is a simplistic task is a key driver of the low value that is placed on reporting.?It is also one of the reasons I think most organizations actually get BI wrong.?

The next assumption that drives the Oversimplification Paradox is that for most organizations, mediocre reporting seems good enough. The value of reporting is most often tied to descriptions of what happened in the past. There is rarely any expectation of analytic insight, advanced analysis, or transformation. These are reports that are merely okay. People want their reports so they can see what happened. But at the end of the day, reporting like this does not transform a business. These reports are critical – don’t get me wrong. But in this mindset, reports are nowhere near what Business Intelligence has the potential to do.

The final assumption in the Oversimplification Paradox is that because reports are easy to do and because mediocre reporting is good enough, it follows that reporting should be a low-cost afterthought. Of course not all businesses operate this way but a surprising number do.

I can’t count the number of clients who talk about how many great things they want to do around reporting and analytics in the future. It is always some distant time when the financial resources to get reporting right will materialize magically. As someone who has seen the power of true Business Intelligence and its ability to transform companies, this line makes me want to cry. Whenever I hear it, I marvel at the inability to see past the immediacy of the current quarter.

Want examples? I worked with a manufacturer, one generating many hundreds of millions in sales and they had the potential to get really deep on targeting buying behaviors as it relates to their supply chain. They were just starting down the path of bringing in a whole new data source and the only thing they wanted to do was to describe the data. They wanted to see variance and nothing else. I tried getting them to understand that we could start down the path of analyzing the key drivers of that variance before moving on to predicting how sales behaviors might change. They loved the idea but felt that they could never get the money to do this. They also felt that eventually, they could do all the analysis they needed themselves in Excel. The Oversimplification Paradox at work!

Want another example? I once worked with a healthcare organization that had?a newly minted college grad building reports for them. They wanted to understand cost drivers for the hospital, especially ones that had underwhelming reimbursement. They wanted this all done in Excel (again with Excel). When asked to examine a data warehouse with analytic capabilities, their response was that Excel was sufficient. And really, this was just a nice-to-have - definitely not mission critical!

I could go on. Both of those are glaringly obvious examples. But the Oversimplification Paradox shows itself in subtle ways all the time. Companies underinvest in analytics and BI. They do not see the value in putting resources towards such things. And then when the results come back as mediocre, they feel vindicated in their beliefs.

The Foundation for BI and Business Analytics is Often Bad Data

Since I’ve lived lots of my professional life in sales, I’m going to focus on CRM in my examples.?However, the applies to any data heavy applications.

If I had to venture a guess at the number one sin committed by sales organizations, at least in respect to their use of technology, it is poor CRM adoption and usage. The best designed and best intended CRM is still only as good as the users who put data in. Many companies suffer from poor adoption and usage. And this presents itself in a couple of ways. First, some users just don’t use the system at all. Second, some users put in the minimum data possible. And third, some users put their data in at the last second possible (“Late breaking news!”) In all three cases, the CRM is not doing what it was intended to do - paint an accurate portrait of future sales performance.?

Let’s pause for a moment to consider what I mean by adoption. I do not merely mean keystrokes on a form. That is the barest minimum of getting data into CRM. However, real customer relationship management involves getting the right data at the right time to help further the closing of sales.?

That means understanding leads, opportunities, proposals, etc. It involves understanding and tying together support cases, field service, marketing, and other formal and informal interactions with clients. And the greatest usage of CRM works with sales, marketing, and customer support to add significant value to daily work. It helps predict the next action people should take to improve success. It should enable continuous data gathering, both passive and active, that captures and drives action and a holistic picture of clients.

Does that sound like the typical CRM??

Or does that sound like the CRM application organizations may have wanted and maybe even were “sold” but did not receive??

I’ve worked with some amazing companies and I’ve seen fantastic implementations of CRM systems. And in most organizations, the focus was on how to get the company to use CRM. It was not on building the most complex, feature rich system imaginable. Rather, it was on finding ways to drive usage amongst the most sales, marketing, customer support, and field service employees possible. And in turn, this enabled far better BI and analytics.?

The reward for sales, marketing, and others? Higher close and win rates. Better targeted marketing campaigns. Sales intelligence and efficient process automation. Happier customers AND employees. Greater success.

In the above examples, good design leads to good data. And good data leads to good analytics. The corollary is that bad data leads to poor analytics. And as stated, most organizations are sitting on piles of bad data! This is not a problem without a solution. Rather, this books helps focus on building the incentives and reasons for why getting to good analytics really matters.