Cloud 9

  • September 7, 2011
  • Forecasting and pipeline management don’t get nearly the attention they deserve and that doesn’t make sense.  Of all the parts of CRM, the forecast is one of the few things many companies still leave to manual systems, i.e. spreadsheets.  Even sales compensation has a higher place in heaven as companies like Xactly have blazed a trail away from spreadsheets to a system with a database and analytics, with excellent results.  You’d think that sales people would be willing to invest as much in the forecast as they do in counting their commissions.

    Part of the challenge with forecasting and pipeline management is that some professionals might resent conventional forecasting systems for the same reasons they like compensation systems.  Confused?  You shouldn’t be.  Both types of system reduce uncertainty to certainty as much as possible.  But while that’s a good thing when you are counting existing money (your commissions), it’s a problem when figuring out the future because the future is anything but certain.

    That’s why last week’s Cloud 9 Analytics user meeting was so important.  At their third annual user conference, CEO Jim Burleigh, talked about the importance of understanding the probabilities when forecasting.  It’s no coincidence that Cloud 9 now boasts a forecasting user interface that uses probabilities but also acts like a sales manager.

    If you’ve spent any part of your career in sales then you know there are deals and there are DEALS.  Some deals are like racehorses, they practically sprint from first call to closure while others plod along and maybe even stop.  That’s an extreme situation and it’s easy to spot the real winner.  But consider two deals at a 90 percent completion stage.  They might look the same numerically but each took a different path to that 90 percent mark.  One might have taken twice as long, one might not have enough money budgeted, one may be run by a C-level officer on the customer side the other might be managed by a director.

    These differences in the history of the deal add up and a seasoned sales pro knows they are important.  But conventional pipeline and forecasting tools (e.g. spreadsheets) make no use of history, which might help explain why only nine percent of organizations we’ve surveyed have a 0.9 correlation between the forecast and reality.  The rest?  Foregtaboutit.  When it comes to forecasting these deals, the sales pro might favor one over the other for reasons that add up to gut instinct.  So, it’s no surprise that the pros create three flavors of forecast — the best case, worst case and the most probable.

    The genius of Cloud 9 today is that they’ve found a way to take the best of what analytics can do to track history and spot trends and combined it with a forecasting user interface that enables a professional to apply common sense to arrive at best, worst and most probable scenarios.  Some people call it gut instinct and I suppose that’s as good a term as any, but really, it’s not gut — it’s applied intelligence and experience that just happen to be hard to put into words.  At any rate, the new forecasting UI is straightforward and looks easy to use and it will remind professionals of their beloved spreadsheets, but with a lot more intelligence behind it.

    Getting sales people to put aside the pure spreadsheet approach and go with something with more rigor behind it may still be a challenge.  But Cloud 9 has demonstrated that it both understands the challenge in all its dimensions and that it can turn its knowledge into very serviceable product.  Like the compensation managers before them, Cloud 9 has replaced the spreadsheet with something that makes more sense, is easier to use and should result in better results all around.

    Published: 6 years ago


    A couple of weeks ago, Marketo announced its research-based belief that its form of revenue performance management (RPM) could help grow global GDP by $2.5 trillion by 2015.  I love it when emerging companies talk about big plans this way.  It reminds me of the young plumber who upon seeing Niagara Falls for the first time says, “I think I can fix it!”

    But there’s something to this proposal that ought to be taken seriously and when you talk about trillions of dollars you are presumably talking seriously.  Global GDP in 2011 is predicted at $68.65 trillion by the International Monetary Fund and the Marketo announced figure was spread over three years.  But that’s a lot of improvement no matter.

    To put this into perspective you have to back up and ask about the assumptions involved and Marketo was kind enough to anticipate the questions and perform a little research.  According to the announcement, Marketo did some analysis of its customers’ revenues as they took advantage of the company’s marketing automation, sales effectiveness and analytics tools.

    Side note: No one’s crown jewels were harmed in the analysis.  Having a big pile of relatively homogeneous data for analysis is a side benefit of multi-tenant cloud computing.  Multi-tenant cloud computing could provide important analytic benefits like this to all users if we could only 1) Put down some ground rules governing the use of the aforementioned crown jewels, thus creating a data commons; and 2) Get over our hang-ups about maintaining the pristine nature of our data in clouds.  Really, it’s like the five year-old who can’t stand seeing the peas touching the mashers on the plate.  But I digress.

    The three tools, marketing automation, sales effectiveness and analytics, combine to provide the tools a company needs to implement revenue performance management strategies.  RPM is still a relatively new idea but other companies like Eloqua, with whom Marketo competes and Cloud 9 Analytics (a Marketo stable mate in venture capitalist Bruce Cleveland’s menagerie) are conspiring to give the idea critical mass.

    In the nub, RPM is simply about using the data that is routinely given off by our business processes as fodder for the analytics engine.  Too often the data goes unused or simple reporting engines choke on the abundance.  But an analytics engine spits out all kinds of ideas like what to offer the customer based on its experience, or generally offering insight that a human eye might miss but which a statistical model would discover easily.

    So, two and a half trillion bucks over three years averages out to a bit less than one percent a year.  In percentage terms that is not much but the existence of all the zeros in a trillion will get your attention.  After all, that’s growth and incremental improvements like this are how markets and economies grow.

    More importantly, the ROI can be stunning.  Given the fact that RPM would not be applied evenly across big corporations and lemonade stands, the places where it could make a difference would notice the change.  Moreover, the cost of implementing RPM where it’s needed would be much less than the incremental gains, especially with modern cloud computing delivering the tools cost effectively.

    I am not an expert on RPM, yet.  I am more like the one eyed man in the land of the blind.  But my thought is that we ought to get familiar with this idea, which is essentially applied analytics.  Our economy is still climbing out of the recession and the jobs numbers that I have seen for May are disappointing.  Every recession ends with some new product or idea taking off and leading the way.  I haven’t seen the big new idea yet but maybe this is it.  Regardless, a little investigation won’t cost anything.

    Published: 7 years ago