Magic Quadrant

Magic Quadrant (MQ) is a series of market research reports published by IT consulting firm Gartner that rely on proprietary qualitative data analysis methods to demonstrate market trends, such as direction, maturity and participants.[1] Their analyses are conducted for several specific technology industries and are updated every 1–2 years: once an updated report has been published its predecessor is "retired".[2]

Rating

Gartner rates vendors upon two criteria: completeness of vision[1] and ability to execute.[1] Using a methodology which Gartner does not disclose, these component scores lead to a vendor position in one of four quadrants:

  • Leaders – Vendors in the Leaders quadrant have the highest composite scores for their Completeness of Vision and Ability to Execute. A vendor in the Leaders quadrant has the market share, credibility, and marketing & sales capabilities needed to drive the acceptance of new technologies. These vendors demonstrate a clear understanding of market needs, they are innovators and thought leaders, and they have well-articulated plans that customers and prospects can use when designing their infrastructures and strategies. In addition, they have a presence in the five major geographical regions, consistent financial performance, and broad platform support.
  • Challengers – A vendor in the Challengers quadrant participates in the market and executes well enough to be a serious threat to vendors in the Leaders quadrant. They have strong products, as well as sufficiently credible market position and resources to sustain continued growth. Financial viability is not an issue for vendors in the Challengers quadrant, but they lack the size and influence of vendors in the Leaders quadrant.
  • Visionaries – A vendor in the Visionaries quadrant delivers innovative products that address operationally or financially important end-user problems at a broad scale, but has not yet demonstrated the ability to capture market share or sustainable profitability. Visionary vendors are frequently privately held companies and acquisition targets for larger, established companies. The likelihood of acquisition often reduces the risks associated with installing their systems.
  • Niche Players – Vendors in the Niche Players quadrant are often narrowly focused on specific market or vertical segments. This quadrant may also include vendors that are adapting their existing products to enter the market under consideration, or larger vendors having difficulty developing and executing on their vision.

Criticism

It has been pointed out that the criteria for the Magic Quadrant cater more towards investors and large vendors than towards buyers.[3]

Much of the criticism is focused on the lack of disclosure of the money received from the vendors it rates, raising conflict of interest issues. Also a source of criticism is the lack of disclosure on the vendor's component scores and the lack of transparency in Gartner's methodology used to derive the vendor's position on the MQ map.

The Magic Quadrant, and analysts in general, also skew the market: according to research,[4] by applying their methodologies to describe a market, they change that marketplace to fit their tools.

Another criticism is that open source vendors are not considered sufficiently by analysts like Gartner, as has been published in an online discussion between a VP from Talend and a German Research VP from Gartner.[5]

Gartner was the target of a federal lawsuit (filed May 29, 2009) from software vendor, ZL Technologies, challenging the “legitimacy” of Gartner’s Magic Quadrant rating system.[6] Gartner filed a motion to dismiss by claiming First Amendment protection since it contends that its MQ reports contain "pure opinion", which legally means opinions which are not based on fact.[7] The court threw out the ZL case because it lacked a specific complaint.[8] That decision was upheld on appeal.[9]

gollark: I think the more powerful ones can run stuff like stripped-down Node.js or MicroPython.
gollark: You use C for those mostly.
gollark: It would probably have a microcontroller in it, and those typically run C.
gollark: There's probably some way to rewrite them as a bunch of equations, say, then solve those - you know the amount of X atom/ion on the left is equal to the amount on the right, and you know the amount on the left is equal to (moles of reactant A * 3 + moles of reactant B * 2) and so on.
gollark: I think what humans do is randomly guess a bit, tweak the numbers so they match better, then infer the rest when they reach something consistent.

See also

References
  1. "Magic Quadrants and MarketScopes: How Gartner Evaluates Vendors Within a Market". Gartner.com. February 2008. Retrieved 2009-07-27.
  2. Gartner (2019), Gartner Magic Quadrant: Frequently Asked Questions, accessed 6 June 2020
  3. "Looking beyond the magic quadrant to find the nitty-gritty". Real Story Group. 2009-08-07. Retrieved 2009-08-08.
  4. "Why IT Vendors Should Take Industry Analysts (More) Seriously | Institute of Industry Analyst Relations". Analystrelations.org. 2012-09-26. Retrieved 2015-02-24.
  5. "Vendor complains in a very public blog post about Gartner's Data Integration Magic Quadrant". Sagecircle.wordpress.com. 2009-12-29. Retrieved 2009-08-08.
  6. "Is shooting on the referee productive? | Institute of Industry Analyst Relations". Analystrelations.org. 2009-10-21. Retrieved 2015-02-24.
  7. "ZL v Gartner Complaint". Scribd.com. Retrieved 2015-02-24.
  8. "E-mail Archiving Vendor Takes on Gartner's Magic Quadrant". EnterpriseStorageForum.com. 2009-11-13. Retrieved 2015-02-24.
  9. "Unpublished Dispositions (Memoranda)". Ca9.uscourts.gov. Retrieved 2015-02-24.
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