Five Strategies for Slaying the Data Puking Dragon.

If you bring sharp focus, you increase chances of attention being diverted to the right places. That in turn will drive smarter questions, which will elicit thoughtful answers from available data. The result will be data-influenced actions that result in a long-term strategic advantage.

It all starts with sharp focus.

Consider these three scenarios…

Your boss is waiting for you to present results on quarterly marketing performance, and you have 75 dense slides. In your heart you know this is crazy; she won’t understand a fraction of it. What do you do?

Your recent audit of the output of your analytics organization found that 160 analytics reports are delivered every month. You know this is way too many, way too often. How do you cull?

Your digital performance dashboard has 16 metrics along 9 dimensions, and you know that the font-size 6 text and sparkline sized charts make them incomprehensible. What's the way forward?

If you find yourself in any of these scenarios, and your inner analysis ninja feels more like a reporting squirrel, it is ok. The first step is realizing that data is being used only to resolve the fear that not enough data is available. It’s not being selected strategically for the most meaningful and actionable insights.

As you accumulate more experience in your career, you’ll discover there are a cluster of simple strategies you can follow to pretty ruthlessly eliminate the riffraff and focus on the critical view. Here are are five that I tend to use a lot, they are easy to internalize, take sustained passion to execute, but always yield delightful results…

1. Focus only on KPIs, eliminate metrics.

Here are the definitions you'll find in my books:

Metric: A metric is a number.

KPI: A key performance indicator (KPI) is a metric most closely tied to overall business success.

Time on Page is a metric. As is Impressions. So are Followers and Footsteps, Reach and Awareness, and Clicks and Gross Ratings Points.

Each hits the bar of being “interesting,” in a tactical oh that’s what’s happening in that silo soft of way. None, passes the simple closely tied to overall business success standard. In fact, hold on to your hats, a movement up or down 25% in any of those metrics may or may not have any impact on your core business outcomes.

Profit is obviously a KPI, as is Likelihood to Recommend. So too are Installs and Monthly Active Users, Orders and Loyalty, Assisted Conversions and Call Center Revenue.

Each KPI is of value in a strategic oh so that is why we are not making money or oh so that is why we had a fabulous quarter sort of way. A 25% movement in any of those KPIs could be the difference between everyone up and down getting a bonus or a part of the company facing layoffs. Often, even a 5% movement might be immensely material. What metric can say that?

When you find yourself experiencing data overload, don an assassin's garb, identify the metrics and kill them. They are not tied to business success, and no senior leader will miss them. On the ground, people will use metrics as micro diagnostic instruments, but they already do that.

A sharp focus on KPIs requires concentrating on what matters most. Every business will have approximately six KPIs for a CEO. Those six will tie to another six supplied to the CMO.

After you go through the assassin’s garb process above, if it turns out that you have 28 KPIs… You need help. Hire a super-smart consultant immediately!

2. Focus only on KPIs that have pre-assigned targets.

This is a clever strategy, I think you are going to love it.

Targets are numerical values you have pre-determined as indicators success or failure.

Turns out, creating targets is insanely hard.

You have to be great at forecasting, competitive intelligence, investment planning, understanding past performance, organization changes and magic pixie dust (trust me on that one).

Hence, most companies will establish targets only for the KPIs deemed worthy of that hard work.

Guess what you should do with your time? Focus on analysis that is worth your hard work!

Start by looking at your slides/report/dashboard and identify the KPIs with established targets. Kill the rest.

Sure, there will be howls of protest. It'll be John. Tell him that without targets you can’t identify if the performance is good or bad, a view every CEO deserves.

John will go away and do one of two things:

1. He will agree with you and focus on the KPIs that matter.

2. He will figure out how to get targets for all 32 metrics along all 18 dimensions.

You win either way. :)

An added benefit will be that with this sharp focus on targets, your company will get better at forecasting, competitive intelligence, investment planning, org changes, magic pixie dust and all the other things that over time become key assets. Oh, your Finance team will love you!

Special caution: Don't ever forget your common sense, and strive for the Global Maxima. It is not uncommon for people to sandbag targets to ensure they earn a higher bonus. If your common sense suggests that the targets are far too low, show industry benchmarks. For example, the quarterly target may be 400,000 units sold. Common sense (and company love) tell you this seems low, so you check actuals to find that in the second month, units sold are already 380,000. Suspicion confirmed. You then check industry benchmarks: It is 1,800,000. WTH! In your CMO dashboard, report Actuals, Target and Benchmark. Let him or her reach an independent, more informed, conclusion about the company’s performance.

3. Focus on the outliers.

Turns out, you are the analyst for a multi-billion dollar corporation, with 98 truly justifiable KPIs (you are right: I'm struggling to breathe on hearing that justification, but let's keep going). How do you focus on what matters most?

Focus your dashboards only on the KPIs where performance for that time period is three standard deviations away from the mean.

A small statistics detour.

If a data distribution is approximately normal then about 68 percent of the data values are within one standard deviation of the mean, about 95 percent are within two standard deviations, and about 99.7 percent lie within three standard deviations. [Wikipedia]

By saying focus on only reporting on KPIs whose performance is three standard deviations from the mean, I’m saying ignore the normal and the expected. Instead, focus on the non-normal and the unexpected.

If your performance does not vary much, consider two standard deviations away from the mean. If the variation is quite significant, use six (only partly kidding!).

The point is, if performance is in the territory you expect, how important is it to tell our leaders: The performance is as it always is.

Look for the outliers, deeply analyze the causal factors that lead to them, and take that to the executives. They will give you a giant hug (and more importantly, a raise).

There are many ways to do approach this. Take this image from my January 2007 post: Analytics Tip #9: Leverage Statistical Control Limits

Having an upper control limit and a lower control limit makes it easy to identify when performance is worth digger deeper into. When you should freak out, and when you should chill.

Look for outliers. If you find them, dig deeper. If not, move on permanently, or at least for the current reporting cycle.

Use whichever statistical strategies you prefer to find your outliers. Focus sharply.

4. Cascade the analysis and responsibility for data.

In some instances you won't be able to convince the senior leader to allow you to narrow your focus. He or she will still want tons of data, perhaps because you are new or you are still earning credibility. Maybe it is just who they are. Or they lack trust in their own organization. No problem.

Take the 32 metrics and KPIs that are going to the CMO. Pick six critical KPIs for the senior leader.

Cluster the remaining 26 metrics.

You'll ask this question:

Which of these remaining 26 metrics have a direct line of sight to the CMO’s six, and might be KPIs for the VPs who report to the CMO?

You might end up with eight for the VPs. Great.

Now ask this question:

Which of these remaining 18 metrics have a direct line of sight to the eight being reported to the VPs, and might be KPIs for the directors who report to the VPs?

You might end up with 14 for the directors.


Repeat it for managers, then marketers.

Typically, you'll have none remaining for the Marketers.

Here's your accomplishment: You've taken the 32 metrics that were being puked on the CMO and distributed them across the organization by level of responsibility. Furthermore, you've ensured everyone's rowing in the same direction by creating a direct line of sight to the CMO’s six KPIs.

Pat yourself on the back. This is hard to do. Mom is proud!

Print the cascading map (CMO: 6 > VPs: 8 > Directors: 14 > Managers: 4), show it to the CMO to earn her or his confidence that you are not throwing away any data. You've simply ensured that each layer reporting to the CMO is focused on its most appropriate best sub-set, thus facilitating optimal accountability (and data snacking).

I’ll admit, this is hard to do.

You have to be deeply analytically savvy. You have to have acquired a rich understanding of the layers of the organization and what makes them tick. You have to be a persuasive communicator. And, be able to execute this in a way that demonstrates to the company that there’s real value in this cascade, that you are freeing up strategic thinking time.

You’ll recognize the overlap between the qualities I mention above and skills that drive fantastic data careers. That’s not a coincidence.

Carpe diem!

5. Get them hooked on text (out-of-sights).

If everything else fails, try this one. It is the hardest one because it'll demand that you are truly an analysis ninja.

No senior executive wants data. It hurts me to write that, but it is true.

Every senior executive wants to be influenced by data and focus on solving problems that advance the business forward. The latter also happens to be their core competence, not the former.

Therefore, in the next iteration of the dashboard, add two more pieces of text for each metric:

1. Why did the metric perform this way?

Explain causal factors that influenced shifts. Basically, the out-of-sights (see TMAI #66 if you are a subscriber to my newsletter). Identifying the four attributes of an out-of-sight will require you to be an analysis ninja.

2. What actions should be taken?

Explain, based on causal factors, the recommended next step (or steps). This will require you to have deep relationships with the organization, and a solid understanding of its business strategy.

When you do this, you'll begin to showcase multiple factors.

For the pointless metrics, neither the Why nor the What will have impact. The CMO will kill these in the first meeting.

For the decent metrics, it might take a meeting or three, but she'll eventually acknowledge their lack of value and ask you to cascade them or kill them.

From those remaining, a handful will come to dominate the discussion, causing loads of arguments, and resulting in productive action. You'll have known these are your KPIs, but it might take the CMO and her team a little while to get there.

After a few months, you'll see that the data pukes have vanished. If you've done a really good job with the out-of-sights and actions, you'll notice notice that the focus has shifted from the numbers to the text.

Massive. Yuge. Victory.

If more examples will be of value, I have two posts with illuminating examples that dive deeper into this strategy…

Strategic Dashboards: Best Practices, Tips, Examples | Smart Dashboard Modules: Insightful Dimensions And Best Metrics

You don't want to be a reporting squirrel, because over time, that job will sap your soul.

If you find yourself in that spot, try one of the strategies above. If you are desperate, try them all. Some will be easier in your situation, while others might be a bit harder. Regardless, if you give them a shot, you'll turn the tide slowly. Even one month in, you’ll feel the warm glow in your heart that analysis ninjas feel all the time.

Oh, and your company will be data-influenced — and a lot more successful. Let's consider that a nice side effect. :)

Knock 'em dead!

As always, it is your turn now.

Have you used any of the above mentioned strategies in your analytics practice? What other strategies have been effective in your company? What is the hardest metric to get rid of, and the hardest KPI to compute for your clients? Why do you think companies keep hanging on to 28 metric dashboards?

Please share your ideas, wild theories, practical tips and examples via comments.

Thank you.


  1. 1
    Jessica Hardin says

    You could not have timed this better. We find ourselves in an overburdened environment when it comes to all the data that is flowing into our dashboards and reports.

    We kicked off Project Titan last week to radically simplify the reports as well as the people surrounding all the work that get's done. Do you have any guidance of how we can re-think how the team should be organized to accelerate the gains you've outlined in this post?


  2. 3
    David Hooper says

    Outstanding post!

    What matters vs. what REALLY matters.

  3. 4

    Hi Avinash,

    A couple of thoughts:

    – Dashboards should not be confused with full fledged reports. If you have to keep scrolling in your dashboard, you're probably overdoing it.
    – Not leaving any room for adding commentary in the dashboard [assuming that users will be able to stitch together the cause/effect/actions.
    – Having a very narrow time series trend that might give reasons to panic
    – Inconsistent colour patterns / use of colours in legends

    • 5

      Adil: These are wonderful tips, everyone should follow them in their entirety!

      It is hard to pick favs, but both #2 and #3 will provide immediate benefits. Thanks.


  4. 6

    Hi Avinash,

    We involved the C Suite in the reporting dashboards and had an open discussion – ie by asking them “what is the purpose of our digital channels and the role it supports the business?”

    From here we created a dashboard of monthly goals or KPIs which we report back. We do report metrics but these metric reports are sent to the specific teams involved in the tactics.

  5. 7
    Enis Cooper says

    I love the tip about targets. As the famous saying goes: Aim at nothing and you'll hit it every time!

    We currently have only two targets for our entire digital strategy which would make for a lonely dashboard. This initially worried as to what might happen if I reduced our data puke to two KPIs. You've given me courage that this reduction might be the path to sparking a revolution, rather than feeding the current ugly beast.

    Thank you for pushing us into doing things that are good for us. :)

  6. 8
    Veronica Edwards says

    Avinash you are a mind-reader, this is exactly the article I needed at this exact moment!

    It has been difficult to break down the silos in our company and create a data driven culture where everyone is focused on the right thing. You've given me atleast three ideas that I'd not tried at all and one that I knew about but had not pushed hard enough.

    Appreciate the inspiration.

  7. 9
    Javier Galán Taboada says

    As analyst we always want to have as much information as possible to have everything under control, but sometimes we can lose focus.

    This article is very necessary.

  8. 10
    Aaron King says

    Awesome post Avinash! Data-puking dragon is now in my lexicon.

    Lately I've been using data to automate the writing of sentences about shifts in the critical few KPIs, and it has gone over very well. I'd call it downright transformational. I literally used the phrase "data regurgitation" in a meeting yesterday to describe the 'before' vs. the 'after.'

    A) the reporting squirrels who previously spent hours-upon-hours compiling reports and so-called "insights" now actually spend next to zero time actually compiling data and writing bullets about shifts in KPIs

    B) those same reporting squirrels now have more time to actually answer the question why, and this leads to a much more meaningful and thoughful conversation with external clients and internal stakeholders.

    • 11
      Pavels Kilivniks says

      Hi Aaron,

      Mind explaining what you meant by "using data to automate the writing of sentences about shifts in the critical few KPIs"?

    • 12

      Aaron: It is thrilling to hear how you have taken the company in a new direction on this issue. I can confirm that my experience also suggests that the time savings you are seeing are real and material.

      Pavels: I'm not sure exactly what Aaron used. But there have been tools for example that will look at your Google Analytics data or your database and write out what trends are being reported. "Last week sales were 12% less than the week prior and 10% less than same week last year." I find that this helps a little bit.

      What is even better is for intelligent algorithms to analyze causal relationships between that drop in sales, and write down the reasons that had the biggest impact on the drop. "A drop of traffic in India, lower number of visits to the product pages, and a lack of promotions, in that order, impacted sales -12%." Google Analytics had a beta implementation of something like this in their Intelligence solution, sadly it is dead now.


      • 13
        Aaron King says

        Thanks Avinash.

        Pavels, at my firm we use Domo to connect to, compile, transform, and visualize data. Once we have the data prepared for visualization, we're able to create conditional formulas in order to produce quick summary information in sentence form. For example, I have one summary that reads:

        "With our conversion rate {{UP BY XX%/DOWN BY XX%}}, click volume {{UP BY XX%/DOWN BY XX%}}, and AOV {{UP BY $X.XX/DOWN BY $X.XX}}, we generated {{XX% MORE ORDERS/XX% FEWER ORDERS}} for {{XX% MORE REVENUE/XX% LESS REVENUE}} than the previous week."

        This doesn't fully answer the why (i.e. what you did to influence any change in results), but it gives us a nice summary of the critical input factors (conversion rate, click volume, AOV) that result in the outputs (orders, revenue). For example, if revenue is down, but clicks and conversion rate (and also orders) are up, a drop in AOV will present itself and lead me to ask if there was a big promotion or if some lower-priced product(s) were featured on the home page during a given time period.

  9. 15
    Debbie Roberts says

    Let me be one more vote in favor of the Digital Marketing and Measurement Model. It is a part of our Agency's practice. It helps bring focus that is hard to get otherwise.

    You are absolutely right about smart ignoring. It is difficult to figure out what data to ignore, but as I grow older I find I'm getting better at it.

    Thanks for this great post.

  10. 16

    Thank you for your insight as always,

    For your last point – what is your opinion on providing supplemental write-up to executive summary?

    For client reporting, I have been providing 5-6 bullet point summary with couple graphs followed by couple pages of detailed analysis. There is resistance from colleagues in client-facing roles; they do not feel comfortable having to potentially answer a million questions their particular client might have.

    I agree that, for some of the clients this report will go to, the additional insight will be too much technical detail. Whether that is a valid reason to not provide it – I am not sure of it yet.

    • 17

      John H: Let me acknowledge that there are important nuances in an Agency – Client role that we have to account for. As an example, most clients, sadly, will pay for your services by weight (how many kilograms of reports are you sending us each week). In that case, your incentive is to data puke.

      I applaud your effort to try to do the summary. A couple graphs, for each graph Insights – Actions – Business Impact. This is awesome.

      If the focus of this is on the most important KPIs, and you have solid Actions & Business Impact, the client will only ask questions on how to action recommendations. This saves your client facing roles. If we don't do this though, you end up in a situation were you provide a million things to the client and the client still finds some random rat-hole to go down. :)

      For most Agencies it is easy to get hooked on providing data pukes as they are easy to do, best way to earn $100 per hour. The problem is that then you'll not have a very smart client – they will neither take action, hard to find that in data pukes, nor want analysis. This means you'll never be able to charge $1,000 per hour. Hard as it is, you want to do everything you can to get a client to stop asking for data pukes, that is how you will make a lot more money (by having a lot more impact on the client's business!).


  11. 18
    Jen Shelvin says

    Amazing article Avinash… always love your posts.

    The best tip I believe is instilling a mindset in the company where you only report what's worth reporting. This is illustrated by your tip to only show outliers and to only show KPIs with targets. It is difficult to accomplish this shift in culture. People tend to feel great getting lots of data even if they do nothing with it. It is a battle worth fighting nonetheless.

    Thank you. Keep pushing us.

  12. 19

    Thanks for the article, I have learnt something new!

    My question is what if the C-Suite says targets as many sales as possible? Without a specific number…

    • 20

      Luca: That is a reasonable request from them.

      First, unless you are a small business it is pretty easy to know what your competition is doing. You can use their number of sales as a target. :) Or, your industry associations have numbers. Or, create a target that is 10% more than the growth you've seen in the business in the last two years.

      "As many sales as possible" also is a great opening to ask the question: At what cost? How much budget do we have? Hard questions to answer, but help focus attention on fewer metrics.


  13. 21

    Thanks, once again, Avinash, for simplifying a complex issue.

    I teach analytics in American Marketing Association workshops attended by Directors/Managers/VPs. The most common issue is that every metric is important to different people in their orgs – so they wind up with a massive data puke.

    We’ll take all of these metrics and organize them into Indicators, Generators and Results – placing them on a map for a visual representation. So we’re not excluding (yet) but we are at least prioritizing. Eventually Indicators start to drop off of reports as they (most often) aren’t actually indicating anything based on the Results, which are the KPIs you talk about.

  14. 22

    Nice short blog, Avinash, about reporting.

    What do you exactly mean with point 4 cascading KPI's per role, separate dashboard for CMO/manager/marketer?

    Do your recommend to give insights to a marketer, is a custom data puke not sufficient?

    • 23

      Gerard: In the scenario I painted, the CMO is asking for everything – when they only need a handful of metrics.

      Cascading is a process of taking that CMO everything and distributing them to each layer in the organization for whom those metrics will be meaningful (a KPI).

      For every level, I recommend following #5 in this post (give them text, out-of-sights, and not just a data puke).


      • 24

        I'll understand Avinash.

        But is this not too much for every datalayer in your organisation? Don't you focus on directors/managers?

        • 25

          Gerard: It will depend on the size of the organization. In medium sized ones, there won't be a lot of layers to go through and your work will mostly focus on directors/manager.

          In larger organizations you and I might have to ensure that multiple layers get the best metrics they need (instead of data pukes!).


  15. 26

    Hellooooo Avinash,

    LONG time reader, first time commenter. Your posts have been a tremendous help throughout my career.

    Fair warning this is a long post – TL;DR it's about how to implement completely new metrics/KPIs in your organization and prove their worth.

    So, when I'm reading your posts I have to think long and hard on how to translate your sage-like wisdom into a different industry: News Publishing – although sometimes you mention us which always brings a smile to my face :)

    We recently released our first digital only subscription product, evolving our core business strategy (like most publishers) from ad based revenue to reader revenue. Reader revenue relies heavily on the distinction of your content – why would people pay for your content when there a bazillion other publishers, not to mention the behemoths NYT/WP/WSJ, who cover the same stories you are?

    I work with the editorial team, my job being to use data to help them identify this distinction by understanding what our readers value and how they should use that information in their decision-making process. This is TOUGH and I spend tons of time thinking about how to use analytics to assess the value of editorial content.

    What I've come up with, and my current framework for simplifying metrics, are weighted scores to compare reader value vs editorial value. I've turned 23 metrics weighted into three scores – article score (site article completion rates, email/subscription conversions), social score (shares, social engagement, reader feedback), and editorial score (how did our journalists think we did on distinction?). My hope is that by comparing these we can have a better understanding of the disconnect between reader/editorial value and how we can discover insights to help us drive content toward distinction and eventually subscriptions/cash money.

    So here's my problem: I'm having a super dang hard time coming up with KPIs to measure something as subjective as distinction. Surely it's not as simple as just using new subscribers as our KPI!

    So my question to all you smart people is this:

    What is the most effective way that you've come up with completely new KPIs that your organization has never used before? And then, how do you convince a team of content producers (or whomever your audience is) that the KPIs are useful, and that you aren't telling them how to do their jobs?

    Btw, I'm having a great time re-training my brain to analyze these oodles of fun new metrics :)

    For those of you who took the time to read this, bless you.

    • 27

      Andy: First, I love The Christian Science Monitor. You have a unique voice. I've checked the site for a digital subscription (sadly, the print mag will be wasted) or donation (like I do for Pro Publica) but have found neither. I look forward to the digital option (it is still not there, just checked).

      From my collective experience, I've found compound metrics to be uniquely useless. Underlying things could change dramatically, but a compound metric might not. Or, it can change dramatically and it would take a while to figure out what happened. I find them to be excuses.

      (A deep dive into compound metrics in context of social media: Analytics Tip #25: Decrapify Search, Social Compound Metrics)

      On to your questions…

      For a publishing entity it all comes down to four things: Frequency, Recency, Page Value, Micro Outcomes. In your case, you can segment those two by Current Subscribers and Potential Subscribers (sounds better than Visitors :)). Everything else is a metric.

      You can convince your team of producers to use your KPIs if you can give them the number along with what insights does the number possess, what action would you recommend based on the number's performance, and what impact do you predict will be there. They'll pay attention, and will be happy to hear how to do their jobs better, if that stuff is in there.

      All the best!

      PS: On Media Analytics, one of the best folks to listen to is my friend Thomas Baekdal. Here's one of his recent Plus reports: How Editorial Analytics can Help you Define your Editorial Strategy

      • 28

        Very glad to hear that you appreciate CSM journalism. Our marketing and analytics teams are big fans of yours as well. In fact, we're currently in the process of prioritizing the unsexy fundamentals :) (as you pointed out in not being able to find our digital subscription assets!).

        We also have a great admiration for Mr. Baekdal – thanks for sharing the article on editorial analytics. Much appreciated.

        Btw, if you're interested in taking a look at the digital product, here it is –

        Thanks again!

  16. 29
    Jessica A says

    We use multi-tab scorecards/dashboards. The first tab shows the critical KPIs. If the audience wants to see a bunch of metrics as reassurance, they can click through the secondary tabs.

    To be fair, those secondary tabs do come in handy. Occasionally, we'll get questions about the components of the KPIs (did we include X data set, did we filter by Y criteria, did segment Z skew the results). Including the component metrics on those secondary tabs makes it easier for us to address those questions when they arise and build credibility as analysts.

    • 30

      Jessica: It is nice to hear that your experience with drill downs. Some teams will create online versions of these dashboards, and allow their Users to click-through and drill down to a contributing metric or segment.

      I find that this works when the data is being supplied to a team of Analysts – with expertise to interpret data and identify Insights, Actions and Business Impact of those actions. This approach works less when we are providing data to executives because without the IABI in the tabs, the drill down exercise becomes random (whatever pops into their head).



  17. 31

    Thanks, Avinash…

    Great read, as usual. “Smart ignoring” — I've been using this for years: I have 3 kids. Anything less would have driven me crazy after all this time. Not saying' I'm not crazy now mind you…

    I pay a lot more attention to what my kids say now, now that they done grown up. Turns out, they have something intelligent to say. Nice.

    Being an old generation direct marketer, we've always had too much data. The choice was to pick and act on the data that mattered. It was easier then, today we're just drowning in data. SSDD… As such, the choices today are now exponentially more difficult. But the music is better…

  18. 32
    GabrielArevalo says

    A great collection of ideas for us to steal Avinash. We have used only two of your five strategies, can't wait to try the rest of them with our teams.

    A strategy that has worked for us is to break our team into two pieces. 1/3rd of the team is focused exclusively on executive dashboards and decision making. This team uses most of their time in data exploration, finding causal impact etc. This allows them to be productive in a high-value way. 2/3rds of the team is in service of the lower value tasks like reporting.

    Hopefully slowly over time we can change that balance.

  19. 33

    Thank you for the wisdom Avinash!

    As my organization's measurement strategy matures, I have found that the single biggest leap that we have made is to trim down the amount of information we deliver in our reports and focus on the few, mission-critical metrics.

    This concept can seem counterintuitive to many business cultures. As you mentioned earlier, some organizations fall into a trap of paying for the volume of reports, which incentivizes weekly, monthly, quarterly data pukes. This seems common in environments where a workaholic mentality trumps quality. Pats are given for the hours spent, and no actions are taken based on the reporting. What's worse, some clients actually prefer the data pukes because they get to "cherry-pick" a story that fits their agenda from the 42 metrics provided.. SMH.

    I've recently seen some really fantastic examples of the transformation businesses can see by limiting their focus to KPI-only reports. This happens when EVERY metric reported incentivises actions that make the business better. When this happens actions start to drive the conversation during presentations, data starts to drive decisions and the company starts to see authentic results in the data!

    Here's the formula we've been using for marketing reports, which seems to be working well;
    Page 1 – Executive summary: 2-3 KPI's broken out by marketing channel. "Out-of-sights" about WHY the KPI's went up or down compared to last year.
    Page 3-10: A little deeper, more segmented analysis on each channel. 1-2 KPI trend charts per page; full year vs previous year. (We often don't review pages 3-10 during presentations with execs, and focus on page 1-2).

    We have transitioned all reports to Google data studio, (which has reduced time spent with data capture).

    Everyone seems to love this format, and I can feel the data becoming more powerful and influential in the business!

    • 34

      Justin: Thank you for pointing out the cherry-picking habit in some of our peers. I've sadly seen that a number of times.

      The structure you recommend it a thoughtful one. When I was teaching the Market Motive Web Analytics course, we used this structure for the final dissertation defense. :)

      Thank you for sharing your best practices.


  20. 35
    Saneesh Veetil says

    Hi Kaushik,

    I am an avid reader of your blog and have already started implementing few of your concepts within the capabilities of our small team.


  21. 36
    Clayton Rokosh says

    Hi Avinash,

    Awesome collection of ideas.

    On every visit to your website I learn something new. Thanks.

  22. 37

    I love Occam's Razor because you consistently share valuable content Avinash. This one was no exception.

    Two of the five strategies were new to me. One of which I've already implemented to great results (#2). Rather than waiting for permission, we just did it. As the senior executives saw the value of the few KPIs that had targets the rich conversation made them forget all the other stuff that was not important. :)

  23. 38
    Andrew Gracia says

    Very nice article.

    The idea to cascade analysis to reduce the data puking at the top resonated with me. This is something we have not thought about, and plan to implement is post-haste.

    Thanks for the super quality of consistent content.

  24. 39
    Virginia Parra says

    We've been looking for ways to simplify all of the data available and this post comes at the perfect time!

    There was actually a conversation about whether or not we should get rid of metrics and seeing your point, I can tell we'll be having it again.

    Thanks for the post!

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