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2019 Analytics and BI Magic Quadrant: Are You Using Responsibly?

by Cindi Howson  |  February 27, 2019  |  Submit a Comment

The 2019 Analytics and BI Magic Quadrant published two weeks ago. Are you using it responsibly?

We wait just as anxiously as you do for the MQ to publish. And ironically, after about eight months of work, this one published while I was on a plane with unstable wifi. It felt a little like being late to a movie premier. It goes to show, though, that it takes quite a team to bring an MQ to market, with our editors and production team in charge in the end.

So just as the movies wait for the critics, we eagerly await discussion with clients to see what you think. We read the blog posts and watch the tweets and LinkedIn debates.  You rate the note too, and we have to guess why it’s a 5 or a 1. We use all these interactions to shape an MQ each year.  We will be talking with many of you at our upcoming summits the next few weeks in London and Orlando. I also hope you will join our webinar on March 28 where we will review highlights and take questions.

Some of you have likened the countdown to MQ publication to the countdown to Christmas. I suppose it’s an apt analogy as, over the years, I’ve heard the MQ was a gift, a lump of coal, or one that summoned disbelief. One of my favorites, though, has been an animation of a Little Rascal character who could barely wait (@idigdata, was that yours or was that @oswaldxxl or @micoyuk???).  Below are a few of the misconceptions I’ve seen in recent weeks.

  • It’s emotional, but fact-based.  Appearing in the MQ is an arduous process for vendors, customers who take our survey, and us analysts alike.  I remember when Kurt Schlegel first asked me to join Gartner, he said, “come on, don’t you want to have dots keep you awake at night?”  How right he was.  We put so much data into a model and then watch what comes out.  Vendors don’t decide to be in the MQ or not; they only decide whether to answer our questions or not. We are happy to see vendors do well, and when they don’t, it can be range of disappointment or frustration. Our empathy is not only for vendors – it is also for customers who invest in their products and experts who have invested their careers. But it’s our job to tell the good and the bad. So in writing the MQ, our north star is always the customer, and for me personally, as I analyze and write, I picture those lively conversation with the likes of Sully M, Chris W, Bill F, Steve K and Teresa M that has spanned more than a decade.

  • The Data. Someone asked if we thought about how the data is vague and the uncertainty of an MQ.  I disagree here.  The data is the data and it’s extensive.  Our customer reference survey has 1500+ responses plus spot calls, ~1600 Peer Insights reviews, ~180 product features and RFP (see this toolkit), hours of product video, software testing, vendor questionnaire and briefings, and our own knowledge from the 600+ customer interactions we each do a year. Is it too much data? Sometimes it feels like it is, but analytics and BI buyers are highly educated buyers.  We have to be rigorous. You expect it. And in a fiercely competitive market, we have to call out both the profound and subtle differences.
  • The Art. Where there is some uncertainty perhaps is in what we choose to emphasize.  For example, we look at future trends in the Hype Cycles and Cool vendor notes, and these get factored into the Completeness of Vision placement.  Were we tracking augmented analytics five years ago? Not really. Some of those capabilities were only just coming to market, mainly from startups in 2013.  Or, new this year, we added proactive analytics and benchmarking/data-as-a-service.  The market will decide what has staying power and becomes key buying criteria. And indeed, past success is no guarantee of future success.  There is also how we change the model year to year.  In 2016, we removed traditional BI from the MQ definition – elements of data governance and meta data modeling, in an agile way, remained.  This was a major change.  But we change definitions each year as the market and buying requirements evolve, and as you tell us what parts of the MQ are still confusing to you.  So this year, we gave greater emphasis to having both Mode 1 and Mode 2 capabilities in a single platform (note to George Y – yes, we listen, we noodle, we respond). For all these reasons, we analysts do not love the year-to-year comparisons because the market does not stand still. Even if a vendor did absolutely nothing year to year, the dot would move based on how the model changes. But of course, as some of you have built some animated vizzes for dots over time, we are amused to watch them.  As I’m getting ready for the analytics and BI bake offs, I can liken these changes to when we add a dash of cinnamon or a whole tablespoon. Some changes are subtle, some are stronger.

With all this in mind, I hope you will use the MQ responsibly.  I can only repeat the most common mistakes we see that I hope you will avoid:

  • Looking only at the graphic. Last year, many of you told us you don’t really read the MQ, you just look at the dot position. You may notice, then, that our text is shorter this year. At a minimum, read your vendor write ups and the market overview.  If you read the MQ via PDF, that’s on page 44 (go figure). If you access on gartner.com, it’s in the right pane.

  • Assuming “completeness of vision” is only the product roadmap. The placement along the X-axis does include the vendor’s vision, or roadmap, but it also includes a number of other factors such as market understanding, sales and marketing strategy, and vertical solutions. We may think a vendor has a wonderful product roadmap, but if they aren’t doing well on these other strategic factors, they most likely will land in the Niche or Challengers Quadrant, further to the left.
  • Reading the MQ via a PDF. If you really want to understand all the drivers that go into both axes, use the interactive version. This allows you to set your own weights. For example if you are much more focused on the here and now, maximize product and operations for execution, while minimizing viability and momentum;  Do the same for completeness of vision, maximizing market understanding and lowering everything else.
  • Using Only the MQ. If you rely only on the MQ analytics and BI strategy, you are making a mistake. We know fewer of you read the Critical Capabilities which focuses on the product only.  There are also survey notes, market guides, cool vendors, and so many toolkits to help you on your evaluation.  Use the full body of research when buying products and setting strategy. Better yet, set up an inquiry call so we can guide you through the process. It’s what we are here for, and there are a lot of us!

For sure, I don’t want any of you ever to feel bamboozled in reading the MQ. It’s only one of several tools we have to help you make the best analytics and BI investments.

Happy reading … and interacting!

Regards,

Cindi Howson

 

Additional Resources

Predicts 2019: Data and Analytics Strategy

Data and analytics are the key accelerants of digitalization, transformation and “ContinuousNext” efforts. As a result, data and analytics leaders will be counted upon to affect corporate strategy and value, change management, business ethics, and execution performance.

Read Free Gartner Research

Category: business-analytics  business-intelligence  data-and-analytics-strategies  

Cindi Howson
Research VP
1 years at Gartner
25 years IT Industry

Cindi Howson is a Research Vice President at Gartner, where she focuses on business intelligence (BI) and analytics. Her work includes writing about market trends, vendors and best practices and advising organizations on these subjects. Read Full Bio




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