Why I walked away from Planning Analytics/TM1 (and why I didn't go to any of its competitors!)

For a long time TM1 was my life. After a few false starts in my professional career, with TM1 I finally found something I was good at and, thanks to some amazing support from colleagues and employers, I quickly progressed from clueless beginner to leading large planning projects for multinational companies. As a credible TM1 consultant I was in demand and had a stable career ahead of me.

Fast forward a few years and now I’ve left the stable world of TM1 behind to start Co-Modeller, yet another platform aimed at solving the well publicised problem of corporate addiction to Excel. So, why do we need Co-Modeller when we already have TM1, Anaplan, SAP BPC, Adaptive, Jedox, Prophix, Tagetik, Host Analytics, Vena, Board, Quantrix, and a few others?

The Rise of Self Service

One of the biggest changes in the analytics world over the last 10 years has been the rise of self-service platforms like Tableau, Power BI and Alteryx.

Self-service systems empower businesses to become more agile, breaking free from the weeks- or months- long development cycles of a developer-led system. In the performance management world, I don’t believe that any system that requires model builders to understand things like feeders and sparsity, or to keep track of hundreds of scripts firing in different orders can ever answer this self-service trend. Building TM1 models remains a dark art, which, although great for its practitioners, is not so good for end users in businesses.

And so, with the conclusion that my beloved TM1 was not likely to be the future Tableau of the enterprise performance management space, I started looking at the alternatives with a clear picture of what I thought was needed:

  • It should be connected and collaborative - consistency at scale across many connected users is where spreadsheets fail.
  • It should be multidimensional - regions, time, products, customers, versions, divisions. Companies have lots of dimensions and modellers shouldn’t have to sacrifice dimensionality for performance.
  • It should be possible, and performant, to build an entire model using only formulae
  • Building the model should not be more complex than the model itself - no abstract concepts like sparsity for modellers to worry about!
  • It should be an un-opinionated modelling platform - Users should be able to build any type of model they need - financial, operational, analytical, trading, HR, etc.
  • It should be cloud native - everything should be these days!

After evaluating most of the existing technology, there didn’t appear to be any single solution that answered all of these points well enough. Most ask the modeller to handle sparsity, or are limited in terms of dimensionality as a result of performance. Some are clearly aimed at purely finance use cases — not necessarily a bad thing if that’s what you need. With a strong belief that there is significant demand for self service collaborative planning and modelling, we started thinking…

How hard could it be?

… actually pretty hard as it turns out! But after some time, with an exceptional software engineering team and gallons of strong black coffee, we’ve now got the core functionality of Co-Modeller up and running, and I’m delighted to report that I think we answer the above points. We’re not quite ready for public launch yet, but we have already used Co-Modeller to implement some pretty large and complex models for some pretty large customers with great results.

In this blog we will cover the various aspects of what we think makes Co-Modeller special and how we’re progressing with the product ahead of general release. Subscribe to our newsletter to be kept up to date on progress, beta trials and more.

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