Common sense solutions to simple problems

Have you ever looked at a problem and immediately known how to solve it?

Have you ever seen that there’s already a group of people who are responsible for solving this problem this problem, and although they’re working on a fix they obviously have not seen the common sense solution that is so apparent to you?

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I knew we could park here! Problem solved!

Yeah[1].

In situations like these, there are three[2] potential reasons for what you’re seeing:

  1. The other people are just too stupid to to see the simple and obvious solution that’s been sitting right under their noses all this time.
  2. The other people, due to the time that they have spent closely examining the problem and potential solutions, have realized that the simple and obvious solution doesn’t actually address the problem – even though common sense suggests that it should – or that the solution has unintended side-effects that outweigh its benefits.
  3. The other people are responsible for additional problems and solutions across a broader or more strategic scope, and although the simple solution may make sense in isolation, implementing it has been deferred to enable work on other, higher priority problems.

(At this point I feel compelled to point out that this is something I’ve thought about for decades, and I’ve had a draft blog post on this subject for almost a year. I’m not trying to subtweet[3] anyone. I’ve had several people recently reach out to me to make sure that they’re not the reason I tweet periodic reminders that lazy communication is theft, so a disclaimer here feels appropriate.)

In my experience, many people seem to automatically gravitate to the first choice, and that bias seems exacerbated by differences in perspective. If the observer is in a business group and the solution team is in IT – or vice versa[4] – it’s easy for them to miss the complexity and nuance in something that appears simple and straightforward from the outside.

Part of this challenge is inherent in this type of relationship. It’s natural and appropriate to hide internal complexity from external stakeholders. I’m pretty sure I even learned about this in college… not that I remember college[5].

But part of it is the choice we make when we engage in the cross-team relationship. Every time we see a “simple problem” with an “obvious” or “easy” or “common sense” solution we get to decide how to react. We can assume that we know everything important and that the “other guy” is an idiot… or we can consider the option that there might be something we don’t already know.

The choice is ours.


[1] This is less of an actual footnote than a tool to enforce a dramatic pause as you read. Assuming you read footnotes as you go through the post, rather than reading them all at the end. I may need more telemetry to better understand use behavior. Why aren’t any simple problems actually as simple as they first seem?

[2] If you can think of other reasons that aren’t just variations on these three, I would love to hear about them in the comments. My list used to only include the first two reasons, but over the last few years I’ve added the third.

[3] Sub-blog? is that a thing?

[4] There are scores of other variations on this theme – I picked this one because it’s likely to be familiar to the people I imagine read my blog.

[5] Maybe this?

Where has the time gone?

My last post was apparently my 100th post since BI Polar kicked off last October.

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That’s an average of right around two posts per week, although my actual writing output has been much less even and predictable than this number might suggest.

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After 100 posts and a little over one year, where should BI Polar go?

What are the topics you would like to see emphasized in the next year and the next hundred posts?

For the past month or so I’ve been sticking to a three-posts-per-week schedule, but I don’t know how sustainable that is. I’m thinking about switching to a Monday-Wednesday schedule, with one post each Monday to accompany the week’s new YouTube video, plus one additional post each week. This feels like a much more reasonable long-term plan.

So… what topics or themes are you interested in? What would you like to see more of, based on what you’ve seen over the last year? I can’t promise I’ll do what you want, but I can promise that I’ll read every comment, and I expect I’ll be inspired by whatever ideas you have…

It all comes down to culture

I talk about data culture a lot, and in my presentations I often emphasize how the most important success factor when adopting a tool like Power BI[1] is the culture of the organization, not the tool itself.

I talk about this a lot, but I think Caitie McCaffrey may have just had the final word.[2]

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I don’t think that Caitie was talking about the enterprise adoption of self-service business intelligence, but she could have been.

In my day job I get to talk to leaders from large companies around the world, and to see how they’re adopting and using Power BI, Azure. Before today I didn’t think of Moby Dick – I thought of Leo Tolstoy’s classic Anna Karenina, which starts with this classic line:

All happy families are alike; each unhappy family is unhappy in its own way.

Although the details vary, large companies that have successfully adopted managed self-service BI at scale have cultures with important aspects in common:

  • Leaders empower business users to work with data
  • Leaders trust business users to use data to make better decisions
  • IT supports business users with platforms and tools and with curated data sources
  • Business users work with the tools from IT and the guidance from leaders, and work within the guardrails and guidelines given to them for this use
  • Business and IT collaborate to deliver responsive solutions and mature/stable solutions, with clearly defined responsibilities between them

Companies that are successful with managed self-service BI do these things. Companies that are not successful do not. The details vary, but the pattern holds up again and again.

How do these roles and responsibilities relate to culture?

In many ways a culture is defined by the behaviors it rewards, the behaviors it allows, and the behaviors it punishes. A culture isn’t what you say – it’s what you do.

In the context of BI, having a culture with shared goals that enable business and IT to work together with the support from the company leaders is the key. If you have this culture, you can be successful with any tool. Some tools may be more helpful than others, and the culture will enable the selection of better tools over time, but the tool is not the most important factor. The culture – not the tool – inevitably determines success.

This is not to say that BI tools should not improve to be a bigger part of the solution. But to paraphrase Caitie… maybe you should let that white whale swim past.

 


[1] But definitely not only Power BI.

[2] He says unironically, before writing many more words.

BI is dead. Long live BI!

As I was riding the bus home from jury duty the other day[1] I saw this tweet come in from Eric Vogelpohl.

 

There’s a lot to unpack here. and I don’t expect to do it all justice in this post, but Eric’s thought-provoking tweet made me want to reply, and I knew it wouldn’t fit into 280 characters… but I can tackle some of the more important and interesting elements.

First and foremost, Eric tags me before he tags Marco, Chris, or Curbal. I am officially number one, and I will never let Marco or Chris forget it[2].

With that massive ego boost out of the way, let’s get to the BI, which is definitely dead. And also definitely not dead.

Eric’s post starts off with a bold and simple assertion: If you have the reactive/historical insights you need today, you have enough business intelligence and should focus on other things instead. I’m paraphrasing, but I believe this effectively captures the essence of his claim. Let me pick apart some of the assumptions I believe underlie this assertion.

First, this claim seems to assume that all organizations are “good w/ BI.” Although this may be true of an increasing number of mature companies, in my experience it is definitely not something that can be taken for granted. The alignment of business and technology, and the cultural changes required to initiate and maintain this alignment, are not yet ubiquitous.

Should they be? Should we be able to take for granted that in 2019 companies have all the BI they need? [3]

The second major assumption behind Eric’s first point seems to be that “good w/ BI” today translates to “good w/ BI” tomorrow… as if BI capabilities are a blanket solution rather than something scoped and constrained to a specific set of business and data domains. In reality[4], BI capabilities are developed and deployed incrementally based on priorities and constraints, and are then maintained and extended as the priorities and constraints evolve over time.

My job gives me the opportunity to work with large enterprise companies to help them succeed in their efforts related to data, business intelligence, and analytics. Many of these companies have built successful BI architectures and are reaping the benefits of their work. These companies may well be characterized as being “good w/ BI” but none of them are resting on their laurels – they are instead looking for ways to extend the scope of their BI investments, and to optimize what they have.

I don’t believe BI is going anywhere in the near future. Not only are most companies not “good w/ BI” today, the concept of being “good w/ BI” simply doesn’t make sense in the context in which BI exists. So long as business requirements and environments change over time, and so long as businesses need to understand and react, there will be a continuing need for BI. Being “good w/ BI” isn’t a meaningful concept beyond a specific point in time… and time never slows down.

If your refrigerator is stocked with what your family likes to eat, are you “good w/ food”? This may be the case today, but what about when your children become teenagers and eat more? What about when someone in the family develops food allergies? What about when one of your children goes vegan? What about when the kids go off to college? Although this analogy won’t hold up to close inspection[5] it hopefully shows how difficult it is to be “good” over the long term, even for a well-understood problem domain, when faced with easily foreseeable changes over time.

Does any of this mean that BI represents the full set of capabilities that successful organizations need? Definitely not. More and more, BI is becoming “table stakes” for businesses. Without BI it’s becoming more difficult for companies to simply survive, and BI is no longer a true differentiator that assures a competitive advantage. For that advantage, companies need to look at other ways to get value from their data, including predictive and prescriptive analytics, and the development of a data culture that empowers and encourages more people to do more things with more data in the execution of their duties.

And of course, this may well have been Eric’s point from the beginning…

 


[1] I’ve been serving on the jury for a moderately complex civil trial for most of August, and because the trial is in downtown Seattle during business hours I have been working early mornings and evenings in the office, and taking the bus to the courthouse to avoid the traffic and parking woes that plague Seattle. I am very, very tired.

[2] Please remind me to add “thought leader” to my LinkedIn profile. Also maybe something about blockchain.

[3] I’ll leave this as an exercise for the reader.

[4] At least in my reality. Your mileage may vary.

[5] Did this analogy hold up to even distant observation?

Ignorance as a finite resource (or “Data visualization resources”)

I’m not a data visualization professional, nor do I play one on TV. Even though I’ve been working with data professionally for over 20 years[1], I’ve generally been on the back end of systems, working on data platforms and not data visualization. I’ve been known to say on occasion[2] that I’ll make your data sing, but you probably don’t want me responsible for making it pretty. If I’m your report designer, building them will take five times as long, and the reports will suck ten times as much.

Before I joined Microsoft, I worked for many years as a consultant. When working with potential clients, I would often present my ignorance as an asset. This may sound strange, but think about the truth in this simple pitch: “You and your team know too much. There are some questions you will never think to ask, because they’re just too obvious. One of the strengths I will bring to this engagement is my ignorance – I will ask those questions and together we will find answers and build solutions.”

Sometimes ignorance doesn’t feel like an asset – sometimes it just gets in the way. In the past few months this has been the case as I’ve been trying to get build Power BI reports for some of the data I work with day to day. To be more specific, I’ve been trying to build reports that don’t suck. I already have functional reports, but I believe that there are insights waiting in the data that could be discovered and shared more easily if I had stronger data visualization skills. I read documentation, and followed examples and reached out to multiple friends and colleagues or advice and… and often found that not only did I not have the knowledge to effectively visualize my data, I often struggled to effectively communicate my goals. I was both mega-ignorant and meta-ignorant.

Which brings me to the point of this post: I’m hoping to use this monumental ignorance as an asset.

Earlier this week I reached out on Twitter asking for help. I wanted to find resources that could help me build my data visualization skills, and to build my vocabulary of terms and concepts so I could ask better questions. I wanted to address both the mega-ignorance and the meta-ignorance. So I asked both Alberto Cairo[3] and Alyssa Fowers[4] by name, and asked for help in general, and boy did I get it.

I learned one immediate lesson from the replies to this post: I did not do an effective job in communicating my goals. Previously I had struggled when asking for tactical data visualization help; here I was struggling when asking for strategic help, and most of the responses weren’t even close to what I was asking for[5]. This was frustrating, but it validated my understanding of the problem, and reinforced my belief that I need a deeper understanding of the concepts and nomenclature of data visualization if I’m going to improve.

Of the many resources that were shared with me, this one looks the most promising: Andy Kirk’s “Data Visualization: A Handbook for Data Driven Design.” Based on the thoughtful description[6] and glowing reviews, I think this is where I will begin. I’ve pre-ordered the second edition and when it arrives next month I’ll begin my journey…

book

…which is sort of where I was going with this whole post[7]. Ignorance as a finite resource, remember?

I’ve long observed that when one person is struggling with something, he’s typically not alone. When one person asks a question, a dozen other people breathe a silent sign of relief, because they had the same question but didn’t dare ask it. Working under the assumption that I’m not alone in this starting point, I’m hoping to use my current state of ignorance, and the upcoming process of destroying that ignorance, to start a “data visualization as a second language” series of posts.

If you’re looking for excellent tools that you can use today to build on your existing foundation of data visualization knowledge and skills, click on the Twitter link above because there are over a dozen web sites, books, and other resources – and I’m too lazy to copy them all here. But if you’re interested in joining me on my learning journey, stay tuned until August.

Do you think this type of content has an audience? Are you that audience? I’d love to hear from you


[1] How young is too young to play the “old man” card so consistently? Asking for a friend.

[2] Typically these are occasions when someone is looking at one of my ugly reports, and I’m feeling self-conscious.

[3] You may know Mr. Cairo as a leading expert and author on data visualization, as the Knight Chair at the University of Miami, or as the guy who is too busy to replace the lorem ipsum in his bio page, but I will always think of him as the other person who regularly presents on the intersection of data and heavy metal. \m/

[4] If you don’t follow Ms. Fower’s “Data and Dragons” blog you definitely should, because she already has two parts in her “Sword Graphs” series.

[5] Yes, I know this is how Twitter works. I’m trying to be generous here – work with me.

[6] Click on the “Who is this book for” link and tell me that you don’t wish every technical book had this information so readily available.

[7] Brevity will never be my forte.

[8] I was originally thinking of “Data Viz 101” but that sounded too advanced, and if I went with the second idea of  “Data Viz 001”  I know I would forever be making “James Bond’s analyst colleague” jokes. DVSL wasn’t my first choice, but I think I like it.

Writing effective problem reports

If you build software or data solutions[1] you have probably encountered one or both of these situations:

  1. You’re trying to report a bug, but the developer doesn’t believe that there’s a problem.
  2. Someone is trying to report a bug to you, and you can’t tell what the problem is supposed to be.

The problem report has itself become a problem[2].

Fortunately, there’s a simple approach, and simple template, that can make reporting problems easier. This is the template I typically use when I’m reporting a problem and asking someone else to fix it:

Problem: Concise description of problem behavior

Steps to reproduce problem:

  1. First step
  2. Second step
  3. Third and subsequent steps, as necessary

Desired or expected behavior:

4. What I wanted to happen

Observed behavior:

4. What actually happened, including the full details of any error messages

That’s it – simple and easy.

It can also often be helpful to include screen shots, recordings, or other visual resources to supplement the text descriptions. If you use TechSmith Camtasia (commercial, paid) or ShareX (open source, free) or other screen recording software, it can be trivial to record and attach a video – but remember that the video does not replace the written problem report, it supplements it.

I should mention that if you’re a software developer working on a software development team, you probably have a heavier-weight process already[3]. Follow that process. This approach is intended for more casual problem reporting – the sort of thing that you might send to someone in an email asking for help. The sort of email where if you don’t communicate clearly and effectively, the recipient ends up spending more time asking for information than he spends actually answering the question or solving the problem.

Yes, this is why I wrote this post. I hope I never need to link to it…


[1] Or work in a technical field, or use software…

[2] Because I never metaproblem I didn’t like. Yes, this sounded funnier in my head.

[3] If you search for “how to write good bugs” you’ll find a huge number of excellent resources that go into much more depth than this post.

Managing email and work-life balance

I’ll probably never be the most consistent blogger, but WordPress recently made me aware of something: I only blog regularly when I’m taking time off from work.

Streak

I’m back in the office today after a week of part-time work from home[1] and I realized that without making a conscious to do so I ended up blogging every day that I was away from the office.

This insight got me thinking. Specifically, it got me thinking about how I spend my work days, and about how in recent months[2] I’ve been letting my inbox push me around. Although playing a defensive game can work in some contexts[3], I believe I need to adopt a more aggressive posture in this fight.

Starting today I’m trying this approach to Inbox Zero from MVP Luise Freese. I’m hoping that by managing my email more proactively and strategically I can not only be more productive at work, but also have more mental energy and time remaining for blogging.

My teammate Adam Saxton is doing the same thing; he’s a few days ahead of me and is pleased with his progress so far. I’ll check in with him – and with you – next week to see how things are going. Now back to Outlook; I have more items marked for follow-up today…


[1] Part time work from home and full-time feeling old: My older son graduated from high school last week. Where did the years go?

[2] Years.

[3] Please don’t tell Johannes Liechtenauer I said this.