We Interrupt Our Regularly-Scheduled Program…

Rather than talking about HOW to do things with data, let’s start the new year by spending some time on WHY we care about data investments in the first place.

“BORING,” I hear you say, but au contraire!  Even though most of your colleagues have accepted that data is the “trendy” thing, that doesn’t mean they “get it.”  And if they don’t get it, they won’t support (or reward!) you properly.

My goal with this article, then, is to help you convince your colleagues that Power BI (and/or Power Pivot and Power Query) is worth the investment – a hundred times over, actually.  Use this as ammunition.

So if you find yourself saying “hey Rob I already knew all of this,” that’s OK – I’m not talking to the data gene folks here.  For once I’m tailoring these messages to the other 15 out of 16.  (And hey, maybe even you data gene types will take some new ideas away from reading these.)

Principles Guiding this Article

Before diving in to the list itself, it’s important to let you know where I’m coming from.  Here are the principles that I’ll be following as I go through said list:

  1. If you can’t explain it simply, you don’t understand it well enough yet.  I believe in that principle, firmly.  So I’m deliberately going to keep things “Fisher-Price” – no jargon, no esoteric examples.  Just elementary-school-level explanations and illustrations, because defanging complexity is the first step to defeating it.
  2. I’m assuming that your organization has the standard problems.  And this is actually a surprisingly safe assumption, because we’ve found, over the years, that while the specifics vary quite a bit, the fundamental issues are the same old stories, over and over again.  Everyone tends to think “MY organization is uniquely dysfunctional,” but nope – everyone is struggling with the same handful of problems – and those problems are precisely what inform this list.
  3. The ten benefits in this list are well within your organizations’ reach.  You likely already have the right people.  You don’t need to hire (or become) rocket scientists.  You just need a new toolset and a few tweaks to the workflows.
  4. The ten benefits are cumulative, not mutually exclusive.  As in, you can do more than one at a time, and reap massive value. Each one is a big deal on its own, but when you start piling them up, they actually multiply each others’ value.
  5. All ten benefits are readily achievable with the Microsoft suite of tools.  In fact, it’s our years spent applying those tools (Power Pivot, and more recently Power Query and Power BI that have taught us these benefits.  I’m sure you can achieve some degree of these benefits with other tools too, but my personal experience is that the competitive tools are more sizzle than steak (and the MS tools vice versa).

OK, onwards to the list!

Benefit #1: Subdivide and Segment for Effective Action

You know those reports which tell you how things are going “overall?”  The ones which give you ONE set of numbers to represent the entire business?  The ones which lack filter and drilldown?  Those are super common.  We see them everywhere we go (heck, I even saw one on vacation in Florida last week).  Well, they are LYING to you…

Subdivide and Segment for Effective Action

Do you know what Fig. 1 and Fig. 3 have in common?  They both have the exact same average color!  That’s right, the color we call “X” in Fig 1 has an RGB of 96,114,134.  And the average of the RGB’s in figure 3 (weighted by their respective areas) is also 96,114,134!

Well the same thing happens in real life: the top-level average ALWAYS obscures critically-important variation under the surface.  Whether we’re talking about employees, locations, products, services, customers, website visitors…  you name it.  Even if some segments are performing precisely in-line with the overall average, there are other (and important!) segments which are divergent – and in both positive and negative directions.

Yes, the top-level average IS important!  It tells you, after all, where the entire business is heading.  Do we even have a problem, overall?  Are we trending better or worse?  Crucially important to know these things, of course!

But accurate and effective ACTION – aimed at improvement – REQUIRES you to drill down.  Poorly-performing segments, for instance, are the most important to address – why spend time and effort “squeezing” corners of the business that aren’t a problem, and which have less room for improvement?  You may end up even demotivating top performers that way (if the segmentation corresponds to people, which it often does).  No, you need to focus on the problem spots.  And not all problem spots have the same problem – they may need a few different approaches.

As an aside, maybe drilling into the healthy places is a good way to discover HOW they are performing well in the first place!  (And vice versa – you’ll learn a lot from following up on the underperforming segments as well).

Here’s a clearer way to say it:  if you’re trying to improve the numbers on the top-level report, and you’re doing that without drilling down, you’re on a fool’s mission.  Take a step back, breathe, and trust me:  it’s going to be ok.  It’s not hard to produce the subdivided picture, especially not with the Power BI / Power Pivot toolset.  The time spent getting started is not “lost,” but the time you’re spending “squeezing” the whole biz…  yes, that IS lost effort, so stop it.

Benefit #2: Get the Whole Picture in One Place (aka “Stop Drowning in Reports”)

Get the Whole Picture in One Place (aka “Stop Drowning in Reports”)

One of the ways that “data” can get a bad reputation is that too often, we are drowning in it.  Here’s an example:  one of our favorite clients told us, at the beginning of our engagement, that certain managers at their company were receiving hundreds of reports per day…  on a SINGLE TOPIC (customer satisfaction, in this example).

Hundreds of reports per day!  Good gravy how does that HAPPEN?  Well, one factor of course is that traditional SQL-based reports lack drilldown and filter (see Benefit #1), and the “fix” for that weakness is to generate one report for each filter you care about.  Also, there are often multiple source systems containing relevant information on a single topic, and these “silos” of data lead to “silos” of reports (because traditional tools struggle to “see” more than one source system at a time).

And it doesn’t have to be hundreds of reports to be a problem.  Frankly, even five is enough to overwhelm the human brain.  We’re just not built to be computers.

But when you put all of the relevant information in one place, you allow the human/business brain to work as designed (i.e. read, think, act) – as opposed to like a computer (read, remember, switch reports, read, remember…)  And that’s all the difference in the world.

The client in this example is now saving $25 million a year, and can prove it.  Collectively, we unified the disparate silos of data into a single scorecard.  And that’s the difference between “no one has ANY IDEA how they’re doing” and “everyone knows PRECISELY how they’re doing, AND where/how they can improve.”

Speaking of scorecards…

Benefit #3:  Drive Org-Wide Behavior Change with Scorecards

Behavior Change in a Multi-Level Org is a Challenge

Many problems/opportunities can ONLY be addressed by making thousands of small behavior changes, on an ongoing basis, out in the “trenches.”  In other words, there are some which CANNOT be addressed by a small number of smart decisions made at the top of the org.  Improved pricing behavior by the sales force for instance.  Improved quality of service by field technicians, for another.

How do you make that happen?  How do you influence a large number of people to behave differently on an ongoing basis, especially when they operate at a distance (both organizationally and physically) from you?

Fancy management consulting firms charge six-seven figures to do this, but with Power BI and/or Power Pivot, it’s no longer necessary to make that outlay.  We’ve seen organizations crack this nut with in-house resources, modest budgets, and short timelines – even though the impact is absolutely enterprise-wide.  It takes some thought and iteration, for sure, but primarily, you “just” need to build a good scorecard.

A redacted/anonymized example of one of those scorecards appears below.  We enjoyed working with this particular client immensely.  Few things are more satisfying than helping people to solve an “unsolvable” problem, adding millions to the bottom line, and leaving their colleagues wondering “how exactly did they DO that??”

A Real-Life Power Pivot / Power BI Scorecard

A Proper Scorecard Can Facilitate Behavior Change Down Through the Org

And how does this work in practice?  Each manager sits down with their direct reports, usually individually, and goes over the “target” metrics (the color-coded ones) and discuss action plans to turn the red and yellow ones green, while consulting the secondary (non-colored) metrics for a more complete picture.  At higher levels of the org, those direct reports are managers also, and so they repeat this process on down the pyramid.

Notice the Subdivide and Segment theme here?  That’s no accident – I told you these ten things are cumulative in their value!  And guess what?  A good scorecard often also “channels” Benefit #2 (Get the Whole Picture in One Place).  And there are 7 more Benefits to come!

A unified scorecard is a powerful tool for positive change, and while “peak hype” for scorecards happened probably 10+ years ago, today’s modern tools have put it well within your reach.  The Good Idea of yesterday was in fact Good, but technology has finally caught up with it and made it widely accessible and practicable.

Benefit #4:  Eliminate Confusion. Achieve One Version of the Truth.

One Version of the TruthTalking about unified scorecards transitions nicely into the next benefit:  unifying ALL data-driven information, period.  Central IT/BI can never, ever keep up with all the needs of the business, so the business is forced to produce their own reports.  That in itself is not fundamentally a bad thing, but the fragmentation that follows?  Not so great.  Even the definition of supposedly-simple concepts like profitability end up drifting when implemented hundreds of individual times, and that’s before we get into outright mistakes and/or deliberate deception.

“My spreadsheet can beat up your spreadsheet.”  You know this game?  The one where each manager shows up to the meeting with a completely different spreadsheet, each of which is purported to measure the same set of metrics, but they all return different numbers for the same things?  Then the meeting devolves into figuring out whose numbers are correct, rather than the original agenda.

With Power BI (and/or Power Pivot), the ability to generate single authoritative (and well-audited) models, and publish them centrally, is finally in the hands of the Business.  Responsible behavior, efficiency, and everyone pulling in the same direction.  Even IT should rejoice!

Benefit #5:  Free Your Valuable Thinkers from “Spreadsheet Debt Service”

Spreadsheet Debt Service: a Thing of the Past with Power BI

“For someone who is good at Excel, one of the worst things they can ever do for themselves is to create a spreadsheet that is truly useful.”  That’s a joke I tell in my live classes, but it’s based 100% in truth, because anything that’s valuable to the team will require continuous maintenance – and the only way for its creator to escape that responsibility is literally to change jobs.

“Debt service” is a concept from the finance world, and loosely speaking it’s the total cost of interest on all the loans you carry.  There comes a critical level – for an organization or individual – at which the total cost of debt service becomes too high, as a % of total available income/revenue, and after that, the debtor falls into a death spiral, and they get crushed by their debt.

I think there’s a very strong parallel in the world of spreadsheet-driven analysis and reporting, which is where the business world overwhelmingly lives to this day.  The time spent pumping the latest data through these workbooks, as well as making “small” modifications on behalf of their colleagues (cough cough, subdividing and segmenting, anyone?)… it piles up.  And sooner than we’d like, an incredibly-valuable employee and teammate is now spending the majority of their time simply “servicing” their portfolio of spreadsheets!

If you manage one or more of these people, or otherwise depend on them for information, it can be quite confusing and frustrating – “why can’t my people do any more new work?”  It even gets uncomfortable – because “non-Excel people” can’t fathom what’s actually going on in these spreadsheets, there’s little chance of explaining it without sowing the seeds of doubt – is the Excel guru bad at their job?  Have they become lazy?  I’ve seen these perceptions seeping in around the edges many times.  But trust me, your Excel gurus’ pushback is legitimate – there truly IS a breaking point past which your skilled data people simply are “full,” and cannot take on any significant new work.

Now to be clear, I’m talking about traditional Excel here, not “Modern Excel,” because the latter benefits from the Power BI technologies of Power Pivot and Power Query.  Auto-refresh can keep their reports/dashboards up to date with literally ZERO intervention.  In fact, the organization will remain informed with the latest and greatest, even if “the creator” is on vacation.  And we’ve already covered the Subdivide and Segment benefit, which means that they can update instantly produce new takes, and answer new questions, without re-inventing the wheel (which is what traditional Excel forces them to do).

Without hiring a single new person, you can MULTIPLY the work capacity of your data-driven thinkers and purveyors of information.  It’s like “getting them back” again – remember those days before they started saying no?  Of course, the people you will “get back” are FAR more capable than even a team 4x the size as before, working with the old tools.

Benefit #6:  Employ “Fair” Metrics for an Undistorted Reality (aka Apples to Apples)

Employ “Fair” Metrics for an Undistorted Reality The following are all inspired by real examples we’ve encountered in our work:

  1. “We’ve sold 17% more dollars of product X this year!  We should stock more products like that.”
  2. “Sales were down 9% in February, but that’s expected because February is 10% shorter than January.”
  3. “Website traffic was down in April, significantly, looks like those changes we made to the site were a mistake.”
  4. “We sell nearly twice as many dollars of Service A as we do Service B, shouldn’t we push Service A more than Service B?”

Well, in reality, there were extenuating circumstances distorting each of those pictures.  Respectively:

  1. Product X was stocked in 25% more stores this year than last, AND the unit price went up 4%, so in reality, units per store were down significantly, rather than up, indicating that consumer preference might be shifting AWAY from this product.
  2. Once you account for weekends and holidays, in that particular year, Feb and Jan BOTH had 20 “open for biz” days, so on a per-day basis, Feb WAS in fact terrible.
  3. April is a “down” month for this segment of the web EVERY year (thanks to Spring Break), so on a year-over-year basis, this was expected rather than a crisis.
  4. In terms of margin (revenue minus the “wholesales” cost of the service), Services A and B are nearly-identical, so maybe leave them alone, or perhaps “favor” Service B rather than A given its higher margin percentage.

More often than not, raw revenue dollar figures paint a distorted picture, so why is “Revenue $” so often the first column in our reports and dashboards?  Well, only because it’s the easiest thing to count.  Our accounting and billing systems already deal with precisely those numbers, so we get them in that form to begin with.  And with older tools, it’s simply just…  exhausting to perform multi-source/multi-variable calculations (ex: divide by number of days we were open for biz).  Not so with the new tools!

Subtracting cost to serve, dividing by number of days we’re open, etc. isn’t rocket science – far from it!  It’s just a failing of the old tools.  I love telling people that for a living, I perform analytics that return millions of dollars of ROI in short order, and yet 99.9% of the time, the math employed never goes beyond 5th grade level.  The modern tools aren’t better at math, they just make things infinitely more convenient – they let you feed the right numbers into your usually-simple math at the right time.  Revolutionary!  Kinda begs the question doesn’t it…  what took so long?  (Short answer:  in this case, the software industry was the tail that wagged the real world’s dog, but that’s a tale for another day).

Are undistorted metrics crucial to good scorecards?  You betcha!  And being able to subdivide and segment your undistorted metrics is important too, as is seeing undistorted metrics from multiple facets of the business in one place, etc.  Getting the spirit of this game yet?  It’s all one big network of wins – each one relatively simple, but the cumulative effect is a Megawin.  (That’s a real metric-system term for “a million wins.”  Seriously, you can look it up.  OK, fine, I made it up.)

(BTW, the importance of undistorted metrics is one big reason why I’ve long believed that visualization is the crucial last mile, but it’s only as good as the metrics you feed into it.  Visualizing distorted metrics is essentially the art of “Getting Deceived Even Faster!”  So buyer beware of anyone telling you that “viz” is THE key.)

#7:  Foster a Virtuous Cycle – A Culture of Better Questions

imageI love how naturally these benefits “flow” from one to the next.  Imagine that you’ve done the following.

  • Given your analysts and data-driven thinkers a lot more time back – time that they can use to innovate (Benefit 5)
  • Whetted everyone’s appetites for compact convenience (Benefit 2) and trained them to always expect they can drill down under any number (Benefit 1).
  • Conditioned everyone to start asking “but hey, is this metric distorting the picture?” (Benefit 6)
  • Transformed data-driven meetings from free-for-alls into focused conversations (Benefit 4).

Once you’ve reached a certain critical mass (in terms of participants who’ve seen the light), those conditions lead to a steady and sustained acceleration – an ongoing improvement in the quality of thought in your organization.  People see an example of smarter metrics, for instance, and once the value dawns on them, they want to apply that same kind of thinking on other problems.  Which inspires someone else, and on down the line.  And then some day, someone revisits the original smart metrics and says “hey I bet we can improve these too!”  It happens.  We’ve seen it repeatedly.  And heck, it even happens with our own internal analytics.

The data tools have long limited the questions we can answer, which has in turn subconsciously limited the questions we ask.  Once you take the restrictions off, it takes some time for humans to explore those unseen “regions” in their minds and in the business.  I call it “tearing down the invisible prison.”

And isn’t this what it’s all about?  Data tools aren’t the goal, better and more effective thinking is!  (And action informed by that thinking, of course).  If you wanted to argue that Benefit 7 is the biggest one, I wouldn’t disagree.

#8:  Know Whether Something Helped or Hurt (aka Forensics)

Know Whether Something Helped or Hurt

This one is perhaps obvious once Undistorted Metrics and Subdivide/Segment are second nature, but it’s such a common (and valuable) sort of question that it makes the list.

So you’ve made some sort of change in the business, and now you need to know – did it help or hurt?  Well, sometimes it’s so hard to measure such a thing that organizations just flat-out skip it.  They just trust/hope that it helped.  (Happens more than you’d think).  But even more commonly, the “help or hurt” analysis takes the form of a single top-level (non-subdividable) report populated with raw (“unfair”) metrics.
Yeah, well… if you’re doing it that old way, you may as well flip a coin.  If the overall report says “meh, it had no impact,” that might be masking the reality that a few segments WERE very positively impacted – and you miss a crucial detail that could have been replicated business-wide.  Furthermore, if you’re using raw/dumb metrics, you might be misled by basic seasonality (or some other fluctuation of the calendar).  On net, the impact can be enough to make a positive change look negative, or vice versa.

Well you don’t have to be satisfied with looking at the world through lenses caked with mud.  Not anymore anyway.

And hey, maybe along the way, you’ll inspire others in the org to perform more rigorous forensic testing of their initiatives, too.  You know… a virtuous cycle kind of thing…

#9:  Deploy “Tripwires” – Exceptions and Alerts

Deploy “Tripwires” – Exceptions and Alerts in Power BITwo of my all-time favorite blog posts – Movers and Fakers and Sara Problem – are examples of this benefit, and I’m tempted to get lazy here and just say “go skim those, I’ve been writing this for 20+ hours now and I’m getting tired.”  But no, I’m powering through!  Where’s that coffee pot…

Even in an environment where you’ve fully embraced Benefits 1-8, there’s still a weakness waiting to trip you up from time to time.   Specifically, even with a concise and smart set of dashboards, humans don’t have time to drill down into said dashboards in every possible way, nor can they do so every time the data gets refreshed.  Because of that, you can miss things.

EX: I once heard a horror story about a hospital surgery department that accidentally stopped billing patients for anesthesia.  This was a bug in the billing system and had nothing to do with analytics, but…  analytics didn’t catch it either.  Whoops.  Surgeries were still happening, and bills were being sent (for the hospital stay, for the surgeons’ time, etc.) – but the bills were “light” by some significant percentage.  For months.  I’m sure there was some report somewhere that, if someone were monitoring it, they would have seen the problem.  But clearly…  that wasn’t happening.

Imagine instead if there had been a robotic “Night Watchman” in place – watching, tirelessly, for some exceptional change in either direction.  (This is precisely what the Movers and Fakers post is about, btw, maybe you should go read it heh heh).

Well, the Power BI suite and its cousin Power Pivot in Excel let you do precisely that – email you when something fishy happens.  And while Power BI has some built-in capabilities here, I personally prefer the full-flexibility, formula-based approach enabled by Power Update.  You can even set it up to drill down in thousands of different ways, looking for exceptions at the drilled-down level, or even in combinations like “are there any Location-Product pairings that are spiking or plummeting this week?”

Now that hospital example, while authentic and attention-grabbing, is more extreme than it needs to be.  You don’t need something that big and obvious though – every week there are things we COULD see in our dashboards if we happened to look in the right places, but don’t.  Sometimes the exceptions are positive too.  Wouldn’t it be nice to know about those as well, so you can try to replicate them less randomly?

#10:  Don’t Stop at “Inform.”  Directly Advise Decisions!

Let’s start with a controversial statement:  informing people is 100% worthless.  Does that raise your hackles?  Well, here’s the follow-up:  what we do with data has zero value unless or until it translates into ACTION – into better decisions and improvements.  Aha!  That makes it a trivially-true statement rather than a controversial one, but if you keep that principle clearly in mind, it forever changes your approach to data.

Let’s do this by example:  I once was asked to troubleshoot a report that was running slowly.  It was a PivotTable powered by Power Pivot, so it should have been fast.  But when I looked at it, the pivot itself was more than 100,000 rows long!  Not the source data.  The “report” itself!  And it looked something like this…

World's Worst PivotTable

The So-Called “Timecard Report.”
Imagine 100k Rows of This – Not Source Data.  This Was the End Report.

OK, so, first of all, if it doesn’t fit on one screen, it kinda doesn’t exist.  Stuff that vanishes “below the fold” will almost never be seen, and chances are also decent that even the rows above the fold are too detailed/noisy to be of value.  Don’t do this.  Ever.  It boggles my mind, to this day, that there were human beings staring at this.

But the purpose of this “timecard report” was even more fascinating.  There were dozens of regional managers consulting this, multiple times per day, to see if there were any stores that were empty – as in, no employees showed up for work, and the store is sitting there dark, not generating revenue.

They didn’t need a “timecard report” – they needed the Empty Store Detector.  It could look something like this…

Verblike "Report" - The Empty Store Detector/Fixer

This Whole Thing Would be Empty if All Stores Were Good
(Note the information that directly facilitates the follow-up action of getting in touch
with the missing employee and/or finding a replacement.)

This is a very powerful concept.  It deserves more space than this, and in fact, another one of my favorite blog posts, We Have a Crush on Verblike Reports, awaits you if you’re curious.  Which hopefully you are Smile

Honorable Mentions

A few benefits that didn’t make this list, but more because they wouldn’t “compress” well into a longer list, rather than as a reflection of their value:

  1. Forecasting and Planning – imagine how much better these processes can be if they are “bedrocked” on a far more nimble, accurate, and trustworthy set of analytics.  More articles on this in the future.
  2. What If Analysis – a close cousin of forecasting and planning, you can very readily experiment with various scenarios (ex: interest rates rise by X, price of oil falls by Y, exchange rates fluctuate, you outsource a job function, etc.) without actually “living” them.
  3. Facilitating Better IT/Biz Relations – these tools, unlike their forbears, actually incent and reward cooperation between IT and the business.  The longstanding friction between the two is a direct result of the poor tools available much more so than a clash of personalities – at least when it comes to my sphere of operation (data, analytics, BI, whatever you want to call it these days).
  4. Finding Hidden Correlations – this one falls more under the machine learning/data science heading, and therefore “mushrooms” into its own top ten list, so I stayed clear.  Besides, I see this as the sort of thing you do once you get the “basics” mastered – which very few organizations have done at this point in time.  Get your org deep into the ten benefits above and THEN proceed to the next level – but by that time, you will have already reaped MASSIVE benefits.

Reactions?

I’m even more curious than usual what you think of this article, so please drop me a comment.  Was it helpful?  Too obvious?  Can you imagine using its messages to help get colleagues bought in?  (And if you do that, DEFINITELY report back!)  Did I miss one that you can’t believe I excluded?  Are there ones you hadn’t thought of this way before?  Examples of where these have succeeded or failed?

Drop me a comment.  I intend to be active in the comment thread – but only if you are Smile

Thanks for reading this far, and I hope you are having a great start to 2017.

Rob Collie

One of the founding engineers behind Power Pivot during his 14-year career at Microsoft, and creator of the world’s first cloud Power Pivot service, Rob is one of the foremost authorities on self-service business intelligence and next-generation spreadsheet technology.

This Post Has 90 Comments

    1. That “application” was in the back of my mind, so I’m glad that it struck you as useful. Or even just as a link people can send to others as-is. Any surprises in here, or anything too obvious?

  1. Rob,

    Great stuff!!! Has inspired me to materialize a new report concept than will shed some new light in my area of the business and then present to my boss.

    Your 20+ hour marathon to write this post leaves me without excuse to find the time.

  2. Rob,
    Great Great article. And lots of action when clients ask you just to restate financials with all of the density and no action..and my lack of pushing for more insights for them. I agree with David, a good article to pass on to clients.
    Fran

    1. Thanks Fran! 🙂 Seriously there’s a lot packed into your comment that I’d love to hear more about, either now or in the future after you’ve tried some new approaches.

  3. This article makes me want to shout from the rooftops about the life changing value of Power BI! I’m still working on convincing execs at my company. We switched from MS Office to G Suite about a year ago to save money … barf. (I was able to keep my MS license)
    You mention publishing data models centrally. Would we need to do this via sharepoint? Or are there other ways of publishing data models?

    1. Well then mission accomplished Amy – welcome back BTW!

      No, we’re well beyond the era where SharePoint is a strict requirement for central publishing 🙂 . PowerBI.com cloud is the best option, and supports everything, as long as your folks aren’t cloud-averse (G-suite use means they are hypocrites if so). But we’ve also got a lot of exciting new things happening in the on-prem world, including Excel Services without SharePoint (in the SSRS upcoming release). And then there’s another option still, which is SSAS Tabular on-prem by itself with Excel desktop as front end, but given the G-Suite angle, I think that’s one you can rule out.

      1. Rob

        I discover PowerPivot here in your website in 2015 after a hint from a colleague, it changed my professional life, i am grateful for that, my dashboards are very successful with our clients, no complain here, but as the data grow, the PowerPivot model start to show it’s limitation, the data model needs to be separated from the reports, Avi had an excellent webinar to explain this,

        now i know there are two options either SSAS on premise, or the PowerBI.com, the cloud is not an option, SSAS is intimidating as it needs the IT department, don’t you think that Microsoft has not a compelling story for us, something like a small standalone SSAS server for department use, maybe something like Power BI Desktop PRO, something we can sneak without the IT interventions, I have published the idea here

        https://ideas.powerbi.com/forums/265200-power-bi-ideas/suggestions/17636668-paid-power-bi-desktop-pro

        does it make sense, surely, i am not the only one in this situation ? thanks again and sorry for the rant as it is frustrating now

          1. I know it is silly, SSAS come with SQL SERVER, anything that has the word server, become holly and needs the approval of the IT department, even SQL servers express, it took me 3 months to get approval just to install Power BI Desktop, i am still waiting for them to approve pbix as a file that can be saved in the shared folder.

          2. Ugh. If cloud is not an option and SSAS on-prem is roadblocked… how about Power Update (for auto refresh) combined with, say, a Dropbox or File Folder (as a fallback publishing point)?

  4. Rob,

    This article is brilliantly insightful and timely!

    I’ve just transitioned (moved my family half-way across the country) into a position where my reporting and efficiency experience (mostly using PowerPivot) is the most useful qualification. The organization NEEDS numbers 1-10, and I’ve been able to convince them that the Power BI tools will be the answer to almost all of the questions they’ve had. There’s been a bit of push back since I began though, specifically related to granting me the access I need in order to live up to the expectations I’ve set. Apparently, though my division has bought in, I’m still needing to convince IT/DBA of the practicality of this approach. Hopefully this article will help me in articulating myself more appropriately going forward.

    Thanks!

    1. Bold move Jessy, we salute that kind of conviction and courage! (And we understand).

      I’ve written a number of articles (and parts of articles) about convincing IT over the years, and it occurs to me that I need to write a consolidated summary. In the meantime, use our site search box and look for things like “IT cooperation” and “DBA.”

    1. #10 is, in my experience, one of the least-widely known of all the items in the list. It even took me a couple years of doing this fulltime before it crystallized for me.

      People really light up when they see some examples and it dawns on them.

  5. Love it Rob! Always appreciate new angles to hook the wider audience in. I like the focus on fair metrics and truly understanding the right QUESTION to ask, now that Modern Excel and Power BI can accurately answer them. You revived some GREAT older posts too, thanks for bubbling them back up to the surface!

    1. Thanks Chris! Yeah, I love those particular older posts. We often wonder about posting something like “3 posts you may have missed” or similar.

      1. @Rob Collie
        I’ll do you one better! Publish a data model in Power BI on your website that shows details on this blog! The article tags and authors could be slicers. Throw in a table with hyperlinks to individual articles, and the top 5 most viewed articles for the week.

        Would be a GREAT way to navigate the site. I may even volunteer to help… 🙂

  6. Rob – Picking up on your comment “If you can’t explain it simply, you don’t understand it well enough yet.” – agree. One of my early questions when working with a client is to identify the key KPI’s that are important to manage their business. Answers vary from ‘I want everything’, ‘you tell me’ to ‘Andy these are the three’ (he is a board member of a £500M turnover organisation.

    My experience is to determine measures that connects all elements of the business e.g. at the lowest ‘deliveries per customer’, middle ‘deliveries per division’ senior ‘deliveries for the whole organisation’. Ownership of the data is vital and so reporting is structured so that each organisational level analyses and reports performance, problems and solutions up the reporting chain.

    Thanks for a stimulating article

    Andy

    1. Thanks Andy! I think that quote originally comes from Einstein, but I picked it up from my old friend/mentor/boss David Gainer back when I worked on Excel. And guess what? I was positively terrible at explaining things simply back then. So there’s hope for all of us – if I can be cured, anyone can. (Not saying YOU need to be, obviously. But others…)

  7. Thank you for this amazing article! Very well written! We’re just starting to use PowerBI at my organization, mostly in Fundraising Operations. This article will serve as a great guide for me and my team 🙂

    1. That’s awesome Akilah! Can we talk about “Akilah and the Bee-I?” Man I’m funny. But seriously, 1) that would be a great name for a blog and 2) please report back on how things go with your initiatives 🙂

  8. Once again, a really insightful article. This Data-driven world that we’re in needs this kind of “Step back and think about why.” thoughtfulness. And, you never cease to deliver! (I love that about PowerPivot Pro.)

  9. A really good insightful article. I gave a class at my company last year trying to evangelize others into the data business using Power Pivot, Power BI, etc. I was somewhat successful, but I think I could have been more convincing if I had your points then. But I will be doing this again, and your excellent article will be a big part of my class outline!

    1. Thanks Ronald, would love to hear how it goes, even if that means circling back here and commenting a year from now 🙂

  10. Great article Rob. I’ve been doing this for a long time and it never hurts to go back to the ‘obvious’ and rethink practices. Much appreciated!!

    1. When writing about the “obvious,” the response is either “duh, why you wasting our time” or, as in this case, an article that sets records for page views. I never know for certain which it’s gonna be 🙂

  11. My favorite example was the hospital with “free” anesthesia services. I try to remind myself to employ secondary metrics each time I’m monitoring a primary metric.

    1. I like that – another “obvious” thing that, once you say it, changes your perspective. Always monitor secondary as well as primary metrics. Could be #11.

    1. I agree Alex! But please allow me two caveats. One, the older tools just couldn’t do these things quickly or easily enough. MS tools like the older SSRS and SSAS (MD) for instance, as well as older competitors like Cognos and Business Objects. I think newer, self-service BI tools are a necessity. and 2) I’m absolutely certain that the current wave of MS tools do all of these things quite well. I’m sure the competitors also do so to some degree, but professionally speaking I have yet to see the toolset that makes me want to switch over.

    1. Yes, I believe there WILL be an MDIS, but it will be a few months later this year. And I certainly DO hope to speak again 🙂

  12. What a great, great article! Rob you rock. Very effective communication; I love the visuals! You are like Johnny Appleseed. We can take the seed and run with it to plant these ideas and accelerate the winds of change.
    Thank you, thank you!

    1. Circling back to last week’s comments…. Steve did you notice that the VERY NEXT comment after yours (Dave’s) also referenced the idea of “seeds?” I loved that synchronicity. And thanks for the kind words 🙂

  13. Rob,

    Your Power BI insights are very valuable.

    Thank you for getting us started in 2017 with a clear direction.

    Now how can I convince everyone else in the world the wisdom of your words?

  14. As others have said, a great article to pass on to others (particularly, in my experience, people who request reports that are more raw data than informative). Your point #1 is killer: drilling down adds so much value. In particular, I’ve found raw-number lovers can be reluctant to move to higher level dashboards/charts for fear of “mistakes” being hidden by aggregation – something which drilling down mitigates big-time.

    #6 is also critically important. I’ve found even data people (raw-number lovers) often don’t get the difference between presenting raw numbers vs. adjusting the raw numbers to eliminate noise. I’m often asked to show numbers by month (which makes sense if you want to compare to budget, but makes less sense if you’re comparing months to each other without any regard to seasonality/number of business days/etc).

    1. Isn’t #6 strange? On one hand, understandable that people don’t get it, because it’s been FOREVER incredibly difficult to continually “calc out the noise,” and it’s only become feasible recently to do otherwise. But on the other hand… DUH! COME ON PEOPLE!!! 🙂

  15. What kind of crazy person invests 20+ hours unloading their brain of insights that they should be charging thousands of dollars for? Well, Rob Collie does and that’s why I love coming to this blog. And that’s also why my “PowerPivotPro Debt Service” is crushing me in the sense that I feel deeply indebted to Rob and team for the content that they routinely deliver here.

    1. Awww shucks, thanks Tim! RE: “giving” things away, that’s how it all got started here in 2009, and now we’re possibly the fastest-growing Power BI / Power Pivot training and consulting firm in the country. No reason for us to change our stripes. If anything, it’s time to double down 🙂

  16. I loved this post Rob. I enjoyed how you scaffold the concepts together and build towards better BI applications and thinking!

  17. Rob, I’ve been teaching Excel and consulting with marketing analytics teams for the past ~10 years or so, and your posts never fail to resonate with me. This one is no exception; your points are absolutely spot on, and do an excellent job summarizing the actual challenges that I deal with every day.

    I must say, it’s refreshing to hear someone step back and speak to the fundamental, underlying issues that need to be addressed, rather than pitch the next “cure-all” analytics solution. Good stuff!

    1. Thanks Chris, I really appreciate those sentiments. As a recovering software engineer, my most important new professional skill in the past 15 years is the ability to tell technology to take a seat (in my own mind) and make it listen to the humans. Even fantastic software is never really the “star,” it’s always the people using it. THIS TOOL FIXES EVERYTHING is wrong, even if it actually DOES work out that way. THIS TOOL HELPS YOUR PEOPLE BE THEIR BEST is much more like it.

  18. You know you have a good article when the reader says “yes! Exactly!”. I am pretty sure I said it about 10 times 🙂

  19. My team handles digital media reporting across a number of clients, and we think of our insights in terms of a “WHAT-WHY-HOW” progression. WHAT happened (which is the most primitive form of insight), WHY did it happen (getting better), and HOW can it be used to drive the business forward.

    I’ve found that constantly asking for the “how” has helped to fundamentally change the way our analysts interpret data and communicate with clients.

  20. Always great to read your ruminations. I sent this link to the half dozen youngsters here at the farm who spent the better part of their morning getting schooled on setting goals and action planning. Never a coincidence, Incidentally, Alchemy is open and post it flagged to Starting with a “Sarah Problem” measure… Rock on my friend. Rock on.

  21. I think you’ve done a fine job here Rob in outlining the “soft” benefits. How can we translate these into hard dollars?

    Your anesthesia story for #9 is one way and the empty store detector for #10 another. Can we come up with a compelling and universal example for other areas? How about A/B testing for Forensics? Is there a bottom-line example for #4 (one version of the truth)? I think a mini-case study for each point would help put dollars (or euros, yen, etc) against the various points. Maybe your readers can weigh in with their suggestions.

    Here’s my brief effort for #1, subdivide. (Or any other topic you want to associate it with.) We want to build a new $20MM+ logistics facility which would pull a lot of trucking activity away from our main hospital loading docks – direct vendors, UPS and FedEx would call at the new location and we’d cross-dock to the other facilities. Items that have to go to the main dock directly (e.g. food, controlled pharmaceuticals) would have more delivery windows available as a result. In addition, we could purchase expensive medical supplies in bulk and store them at the facility, getting a better price because of the volume buying.

    We initially presented one big number in expected savings from bulk buys. . It’s a good number, but yet another unsupported promise of cost savings! PowerPivot has allowed us to pull 7 years of purchasing history down to the individual line item (10+ million rows) and segment the purchasing + freight charges by departments, vendors, and other dimensions. While our results are numeric rather than graphic, we now have the VP of Budgeting going over our numbers with the proverbial fine-tooth comb looking to pick holes… and he can’t! All the rollups are there for him to see, he can immediate rank which vendors have the greatest opportunity, we can use calculated columns and measures to show lag times between orders and delivery vs. having stock on-hand, etc etc.

    While we can’t guarantee we’ll get executive approval, having a bulletproof and verifiable data source certainly helps.

    1. GMF – I think this was/is the longest comment on the post, and took the longest for me to respond, accordingly. One “problem” with “good” examples is that, by the time they become broadly-understandable, they often can become too “elementary” to be “wow-inducing.” EX: I once looked at a chain of 8 stores, and found that 3 of the 8 were generating less margin than the costs to operate those stores! So, subdividing yielding a WILDLY unexpected conclusion: close 3 store, make more money. Would that resonate? Or too simple?

  22. “informing people is 100% worthless”… lol that’s catchy
    …. on the flip side with regards to capturing data in the first place I have a saying, “no point capturing the data if you’re not going to report on it”.

    1. …with the caveat that you can’t go back in time and collect once you discover you need it.

      I do understand though that capturing is traditionally expensive. Good database design, plus hardware, can drive the price tag up VERY quickly. For me, this is the primary value of Hadoop – make the capture phase cheap. Doesn’t help in the analysis phase so much – so you pay later when you DO discover an analysis need, but much better to defer the expensive part until you are positive you need it, while keeping your options open.

  23. Great article. Don’t underestimate the importance of #9 as I have experienced problems of not having these reports designed.

    I have got most senior managers adopting powerbi but due to an “error” in their report they are very sceptical of powerbi. The report was designed correctly but poorly inputted data (human error) made the report skewed. Designing error reports should happen simultaneously when a powerbi report is released to ensure the authenticity of underlying data.

    1. Thank you sir! As for next book… need to figure out what the next book IS first! At a high level… “3rd edition” or something different.

  24. Rob,

    I’ve been busy or the last nine months as a CFO for a small business and haven’t been able to develop my Power BI / Power Pivot / Power Query skills — but now I’m beginning to see the light and came back to this site to see what’s new. This Back to the Future article is right on time!

    1. What’s SUPER cool, Ralph, and this isn’t an exaggeration at ALL, is that the tools for small biz and enterprise are now exactly the same. What’s best for you is best for them, and vice versa, and even better, the tools are friendly enough now to be accessible to the majority of us (while still maintaining all of that industrial-strength power, which honestly is just as important with 10k rows of data as with 100M rows).

      Keep us posted! 🙂

    1. Happy to help, and LOVE the username you’ve chosen. As I spent the holidays fishing in Florida, up to my ankles in what most would consider a swamp, I was chuckling about the myth that enjoying such things makes one “backwards.” So silly. I respect my fellow human beings regardless of demographic, consider myself an intellectual, and yet few things make me happier than having my toes in the mud. Why are these popularly considered to be mutually-exclusive?

      Anyway, I like to think that this “contrast” is in some sense crucial to my professional success 🙂

      1. Strumento molto poco conosciuto…..
        Gli informatici sono fermamente convinti che Excel (con Power Q e P) non sia lo strumento adatto per la gestione dei Big Data. Power BI è ancora ignoto alla maggior parte. Pensa che ti scrive è un medico, che deve gestire un reparto e i suoi dati di produttività !! Bye

  25. A great article that I’ll definitely be passing onto my colleagues – the comment that “For someone who is good at Excel, one of the worst things they can ever do for themselves is to create a spreadsheet that is truly useful.” really chimes for me – our team are continually “hired” out to help out with other team’s reporting, creating and updating reports that we wouldn’t have created in the first place and making us de facto “owners” of any future updates – which in turn takes up ridiculous amounts of our time.

  26. Hi Rob – this is a great article, and these points are going to be the basis for our Analytic team’s next monthly meeting. In particular, the spreadsheet debt service. We find ourselves servicing one particular client all the time when they come to us with these little requests to change their report. It’s frustrating and a time drain, to say the least. Thanks for this!

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