Is IBM Getting Out of Enterprise Performance Management?

I noticed that IBM last week sold off several EPM products — IBM Cognos Disclosure Management (CDM), IBM Cognos Financial Statement Reporting (FSR), and IBM Clarity 7 products — to a company called Certent.

This, combined with a pretty weak performance in Gartner’s recent financial and strategic CPM magic quadrants — where IBM landed as Visionary and one and a Challenger in the other, and  a Leader in neither — got me wondering about IBM’s commitment to EPM as a category going forward.  Could Planning or TM1 be next?

Moreover, it wasn’t just the new Gartner magic quadrants where IBM didn’t fare well.  In the Dresner Wisdom of Crowds market study, IBM was bottom-right in the Customer Experience model and was the only vendor entirely left out of (i.e., “outside the magnifying glass”) the vendor credibility model.  And IBM’s ring in the spider chart seems to gotten worse, not better, in 2017 over 2016.

Yes, we all know IBM is quite busy re-branding everything that’s not nailed down Watson, but could they be backing off EPM?

Which got me wondering, as I surfed around IBM’s website, why some products appeared to be first-class “products” while others were found under “marketplace.”  Why is DB2 under analytics products while TM1 is under marketplace?

db2 v tm1

Maybe it’s nothing, but I decided to check around a bit.  My friends in the know seem to believe that IBM remains committed to EPM, but that they view Clarity as a legacy product and were tired of getting beaten by Workiva in disclosure management.  That is, they saw it as a desire to focus more on planning and consolidation and as well things like compensation management.

Me, I’m not so sure.  When companies start pruning in an area sometimes they keep pruning.  And, in general, we don’t see them that much in the marketplace — particularly when you think of the powerhouse that Cognos was back in the day.  And, they don’t seem to be doing that well.  And, Watson is the big future focus.  So, file this under rumor and speculation, but watch this space.

A Look at the Tintri S-1

Every now and then I take a dive into an S-1 to see what clears the current, ever-changing bar for going public.  After a somewhat rocky IPO process, Tintri went public June 30 after cutting the IPO offering price and has traded flat thus far since then.

Let’s read an excerpt from this Business Insider story before taking a look at the numbers.

Before going public, Tintri had raised $260 million from venture investors and was valued at $800 million.

With the performance of this IPO, the company is now valued at about about $231 million, based on $7.50 a share and its roughly 31 million outstanding shares, (if the IPO’s bankers don’t buy their optional, additional roughly 1.3 million shares.)

In other words, this IPO killed a good $570 million of the company’s value.

In other words, Tintri looks like a “down-round IPO” (or an “IPO of last resort“) — something that frankly almost never happened before the recent mid/late stage private valuation bubble of the past 4 years.

Let’s look at some numbers.

tintri p+l

Of note:

  • $125M in FY2017 revenue.  (They have scale, but this is not a SaaS company so the revenue is mostly non-recurring, making it easier to get to grow quickly and making the revenue is worth less because only the support/maintenance component of it renews each year.)
  • 45% YoY total revenue growth.  (On the low side, especially given that they have a traditional license/maintenance model and recognize revenue on shipment.)
  • 65% gross margins  (Low, but they do seem to sell flash memory hardware as part of their storage solutions.)
  • 87% of revenue spent on S&M (High, again particularly for a non-SaaS company.)
  • 43% of revenue spent on R&D  (High, but usually seen as a good thing if you view the R&D money as well spent.)
  • -81% operating margins (Low, particularly for a non-SaaS company.)
  • -$70.4M in cashflow from operating activities in 2017 ($17M average quarterly cash burn from operations)
  • Incremental S&M / incremental product revenue = 73%, so they’re buying $1 worth of incremental (YoY) revenue for an incremental 73 cents in S&M.  Expensive but better than some.

Overall, my impression is of an on-premises (and to a lesser extent, hardware) company in SaaS clothing — i.e., Tintri’s metrics look like a SaaS company, but they aren’t so they should look better.  SaaS company metrics typically look worse than traditional software companies for two reasons:  (1) revenue growth is depressed by the need to amortize revenue over the course of the subscription and (2) subscriptions companies are willing to spend more on S&M to acquire a customer because of the recurring nature of a subscription.

Concretely, if you compare two 100-unit customers, the SaaS customer is worth twice the license/maintenance customer over 5 years.

saas compare

Moreover, even if Tintri were a SaaS company, it is quite out of compliance with the Rule of 40, that says growth rate + operating margin >= 40%.  In Tintri’s case, we get -35%, 45% growth plus -81% operating margin, so they’re 75 points off the rule.

Other Notes

  • 1250+ customers
  • 21 of the Fortune 100
  • 527 employees as of 1/31/17
  • CEO 2017 cash compensation $525K
  • CFO 2017 cash compensation $330K
  • Issued special retention stock grants in May 2017 that vest in the two years following an IPO
  • Did option repricing in May 2017 to $2.28/share down from weighted average exercise price of $4.05.
  • $260M in capital raised prior to IPO
  • Loans to CFO and CEO to exercise stock options at 1.6% to 1.9% interest in 2013
  • NEA 22.7% ownership prior to opening
  • Lightspeed 14.5% ownership
  • Insight Venture Partners 20.2% ownership
  • Silver Lake 20.4% ownership
  • CEO 3.8% ownership
  • CFO 0.7% ownership
  • $48.9M in long-term debt
  • $13.8M in 2017 stock-based compensation expense

Overall, and see my disclaimers, but this is one that I’ll be passing on.

 

The New 2017 Gartner Magic Quadrants for Cloud Strategic CPM (SCPM) and Cloud Financial CPM (FCPM) – How to Download; A Few Thoughts

For some odd reason, I always think of this scene — The New Phone Book’s Here – from an old Steve Martin comedy whenever Gartner rolls out their new Magic Quadrants (MQ) for corporate performance management (CPM). It’s probably because all of the excitement they generate.

Last year, Gartner researchers John Van Decker and Chris Iervolino kept that excitement up by making the provocative move of splitting the CPM quadrant in two — strategic CPM (SCPM) and financial CPM (FCPM). Never complacent, this year they stirred things up again by inserting the word “cloud” before the category name for each; we’ll discuss the ramifications of that in a minute.

Free Download of 2017 CPM Magic Quadrants

But first, let me provide some links where you can download the new FCPM and SCPM magic quadrants:

Significance of the New 2017 FPCM and SCPM Magic Quadrants

The biggest change this year is the insertion of the word “cloud” in the title of the magic quadrants.  This perhaps seemingly small change, like a butterfly effect, results in an entirely new world order where two of the three megavendors in the category (i.e., IBM, SAP) get displaced from market leadership due to the lack of the credibility and/or sophistication of their cloud offerings.

For example:

  • In the strategic CPM quadrant, IBM is relegated to the Visionary quadrant (bottom right) and SAP does not even make the cut.
  • In the financial CPM quadrant, IBM is relegated to the Challenger quadrant (top left) and SAP again does not even make the cut.

Well, I suppose one might then ask, well if IBM and SAP do poorly in the cloud financial and strategic CPM magic quadrants, then how do they do in the “regular” ones?

To which the answer is, there aren’t any “regular” ones; they only made cloud ones.  That’s the point.

So I view this as the mainstreaming of cloud in EPM [1].  Gartner is effectively saying a few things:

  • Who cares how much maintenance fees a vendor derives from legacy products?
  • The size of a vendor’s legacy base is independent of its position for the future.
  • The cloud is now the norm in CPM product selection, so it’s uninteresting to even produce a non-cloud MQ for CPM. The only CPM MQs are the cloud ones.

While I have plenty of beefs with Oracle as a prospective business partner — and nearly as many with their cloud EPM offerings — to their credit, they have been making an effort at cloud EPM while IBM and SAP seem to have somehow been caught off-guard, at least from an EPM perspective.

(Some of Oracle’s overall cloud revenue success is likely cloudwashing though they settled a related lawsuit with the whistleblower so we’ll never know the details.)

Unlikely Bedfellows:  Only Two Vendors are Leaders in Both FCPM and SCPM Magic Quadrants

This creates the rather odd situation where there are only two vendors in the Leaders section of both the financial and strategic CPM magic quadrants:  Host Analytics and Oracle.  That means only two vendors can provide the depth and breadth of products in the cloud to qualify for the Leaders quadrant in both the FCPM and SCPM MQ.

I know who I’d rather buy from.

In my view, Host Analytics has a more complete, mature, and proven product line – we’ve been at this a lot longer than they have — and, well, oligopolists aren’t really famous for their customer success and solutions orientation.  More infamous, in fact.  See the section of the FCPM report where it says Oracle ranks in the “bottom 25% of vendors in this MQ on ‘overall satisfaction with vendor.’”

Or how an Oracle alumni once defined “solution selling” for me:

Your problem is you are out of compliance with the license agreement and we’re going to shut down the system.  The solution is to give us money.

Nice.

For more editorial, you can read John O’Rourke’s post on the Host Analytics corporate blog.

Download the 2017 FCPM and SCPM Magic Quadrants

Or you can download the new 2017 Gartner CPM MQs here.

# # #

Notes:

[1] Gartner refers to the category as corporate performance management (CPM).  I generally refer to it as enterprise performance management (EPM), reflecting the fact that EPM software is useful not only for corporations, but other forms of organization such as not-for-profit, partnerships, government, etc.  That difference aside, I generally view EPM and CPM as synonyms.

The Strategy Compiler: How To Avoid the “Great” Strategy You Couldn’t Execute

Few phrases bother me more than this one:

“I know it didn’t work, but it was a great strategy.  We just didn’t have the resources to execute it.”

Huh.  Wait minute.  If you didn’t have the resources to execute it, then it wasn’t a great strategy.  Maybe it was a great strategy for some other company that could have applied the appropriate resources.  But it wasn’t a great strategy for you.  Ergo, it wasn’t a great strategy.  QED.

I learned my favorite definition of strategy at a Stanford executive program I attended a few years back.  Per Professor Robert Burgelman, author of Strategy is Destiny, strategy is simply “the plan to win.”  Which begets an important conversation about the definition of winning.  In my experience, defining winning is more important than making the plan, because if everyone is focused on taking different hills, any resultant strategy will be a mishmash of plans to support different objectives.

But, regardless of your company’s definition of winning, I can say that any strategy you can’t execute definitionally won’t succeed and is ergo a bad strategy.

It sounds obvious, but nevertheless a lot of companies fall into this trap.  Why?

  • A lack of focus.
  • A failure to “compile” strategy before executing it.

Focus:  Think Small to Grow Big

Big companies that compete in lots of broad markets almost invariably didn’t start out that way.

BusinessObjects started out focused on the Oracle financials installed base.  Facebook started out on Harvard students, then Ivy league students.  Amazon, it’s almost hard to remember at this point, started out in books.  Salesforce started out in SMB salesforce automation.  ServiceNow on IT ticket management.  This list goes on and on.

Despite the evidence and despite the fame Geoffrey Moore earned with Crossing the Chasm, focus just doesn’t come naturally to people.  The “if I could get 1% share of a $10B market, I’d be a $100M company” thought pattern is just far too common. (And investors often accidentally reinforce this.)

The fact is you will be more dominant, harder to dislodge, and probably more profitable if, as a $100M company, you control 30% of a $300M target as opposed to 1% of a $10B target.

So the first reason startups make strategies they can’t execute is because they forget to focus.  They aim too broadly. They sign up for too much.  The forget that strategy should be sequence of actions over time.  Let’s start with Harvard. Then go Ivy League.  Then go Universities in general.  Then go everyone.

Former big company executives often compound the problem.  They’re not used to working with scarce resources and are more accustomed to making “laundry list” strategies that check all the boxes than making focused strategies that achieve victory step by step.

A Failure to Compile Strategy Before Execution

The second reason companies make strategies they can’t execute is that they forget a critical step in the planning process that I call the strategy compiler.  Here’s what I think a good strategic planning process looks like.

  • Strategy offsite. The executive team spends a week offsite focused on situation assessment and strategy.  The output of this meeting should be (1) a list of strategic goals for the company for the following year and (2) a high-level financial model that concretizes what the team is trying to accomplish over the next three years.  (With an eye, at a startup, towards cash.)

 

  • First round budgeting. Finance issues top-down financial targets.  Executives who own the various objectives make strategic plans for how to attain them.  The output of this phase is (1) first-draft consolidated financials, (2) a set of written strategies along with proposed organizational structures and budgets for attaining each of the company’s ten strategic objectives.

 

  • Strategy compilation, resources. The team meets for a day to review the consolidated plans and financials. Invariably there are too many objectives, too much operating expense, and too many new hires. The right answer here is to start cutting strategic goals.  The wrong answer is to keep the original set of goals and slash the budget 20% across the board.  It’s better to do 100% of 8 strategic initiatives than do 80% of 10.

 

  • Strategy compilation, skills. The more subtle assessment that must happen is a sanity check on skills and talent.  Do your organization have the competencies and do your people have the skills to execute the strategic plans?  If a new engineering project requires the skills of 5 founder-level, Stanford computer science PHDs who each would want 5% of a company, you are simply not going to be able to hire that kind of talent as regular employees. (This is one reason companies do “acquihires”).  The output of this phase is a presumably-reduced set of strategic goals.

 

  • Second round budgeting. Executives to build new or revised plans to support the now-reduced set of strategic goals.

 

  • Strategy compilation. You run the strategy compiler again on the revised plan — and iterate until the strategic goals match the resources and the skills of the proposed organization.

 

  • Board socialization. As you start converging via the strategy compiler you need to start working with the board to socialize and eventually sell the proposed operating plan.  (This process could easily be the subject of another post.)

 

If you view strategy as the plan to win, then successful strategies include only those strategies that your organization can realistically execute from both a resources and skills perspective.  Instead of doing a single-pass process that moves from strategic objectives to budgets, use an iterative approach with a strategy compiler to ensure your strategic code compiles before you try to execute it.

If you do this, you’ll increase your odds of success and decrease the odds ending up in the crowded section of the corporate graveyard where the epitaphs all read:

Here Lies a Company that Had a “Great” Strategy  It Had No Chance of Executing

Dear Marketing: Stop Putting the Template Ahead of the Story

I’ve always thought that if marketers wrote newspapers, the famous New York Times headline of August 8, 1974 would have looked like this:

nixon1

Instead of how it actually looked, which was:

pinsdaddy-richard-nixon-resigned-as-us-president-40-years-ago-this-week

What’s the difference?  While both of the above presentations are structured, the newspaper doesn’t let the template get in the way of story.  The newspaper works within the template to tell the story.

I think because marketing departments are so often split between “design people” and “content people,” that (1) templates get over-weighted relative to content and (2) content people get so busy adhering to the template that they forget to tell the story.

Here’s a real, anonymized example:

agf1What’s wrong here?

  • There is a lot of wasted vertical space at the top:  all large font, bolded template items with generous line spacing.
  • The topic section gets lost among the other template items.  Visually, author is as important as topic.
  • There is no storytelling.  There is effectively no headline — “Latest Release of Badguy Product” takes no point-of-view and doesn’t create an angle for a story.
  • The metadata is not reader-first, preferring to remind Charles of his title over providing information on how to contact him.

But there is one, much more serious problem with this:  the claim / rebuttal structure of the document lets the competitor, not the company, control the narrative.

For example, political affiliations aside, consider current events between Trump and Comey.  Like him or not, Trump knows how to control a narrative.  With the claim / rebuttal format, our competitive bulletin would read something like this if adapted to the Trump vs. Comey situation.

Competitive Update:  Team Comey
Trump says:

  • Comey is a coward
  • Comey is a leaker
  • Comey is a liar

But, don’t worry, our competitive team says: 

  • Comey isn’t really a coward, but it is interesting that he released the information through a colleague at Columbia Law School
  • Comey isn’t really a leaker because not all White House conversations can be presumed confidential and logically speaking you can either leak or lie, but you can’t both at the same time.

Great.  What are we talking about?  Whether Comey is a leaker, liar, or coward.  Who’s controlling the narrative?  Not us.

Here’s a better way to approach this document where you rework the header and metadata, add a story to the title, recharacterize each piece of the announcement on first reference (rather than saying it once “their way” and then challenging it), and then providing some broader perspective about what’s happening at the company and how it relates to the Fall17 release.

agf2

This is a very common problem in marketing.  It comes from a lack of storytelling and fill-in-the-template approach to the creation of marketing deliverables.  Avoid it by always remembering to put the story ahead of the template.

Just likes blogs and newspapers do.

Blocking the End Run: Eleven Words to Reduce Politics in Your Organization

People are people.  Sometimes they’re conflict averse and just not comfortable saying certain things to their peers.  Sometimes they don’t like them and are actively trying to undermine them. Sometimes they’re in a completely functional relationship, but have been too darn busy to talk.

So when this happens, how do you — as a manager — respond?  What should you do?

“Hey Dave, I wanted to say that Sarah’s folks really messed up on the Acme call this morning.  They weren’t ready with the proposal and were completely not in line with my sales team.”

Do you pile on?

“Again?  Sarah’s folks are out of control, I’m going to go blast her.”  (The “Young Dave” response.)

Do you investigate?

“You know my friend Marcy always said there are three sides to every story:  yours, mine, and what actually happened.  So let me give Sarah a call and look into this.”

Do you defend?

“Well, that doesn’t sound like Sarah.  Her team’s usually buttoned up.”

In the first case, you’re going off half-cocked without sufficient information which, while emotionally satisfying in the short-term, often leads to a mess followed by several apologies in the mid-term.  In the second case, you’re being manipulated into investigating something when perhaps you were planning a better use of your time that day.  In the third case, you’re going off half-cocked again, but in the other direction.

In all three cases, you’re getting sucked into politics.  Politics?  Is it really politics?  Well, how do you think Sarah is going to feel in when you show up asking a dozen questions about the Acme call?  She’ll certainly consider it politics and, among other things, there’s about a 98% chance that she will say:

“Gosh, I wish Bill came and talked to me first.”

At which point, if you’re like me, you’re going to say:

“No, no, no.  I know what you’re thinking.  Don’t worry, this isn’t political.  It’s not like Bill was avoiding you on this one.  He just happened to be talking to me about another issue and he brought this up at the end.  It’s not political, no.”

But can you be sure?  Maybe it just did pop into Bill’s mind during the last minute of the other call.  Or maybe it didn’t.  Maybe the reason Bill called you was a masterfully political pretext.  Can you know the difference?

So what do you say to Bill when he drops the comment about Sarah’s team into your call?  The eleven words that reduce politics in any organization:

“What did Sarah say when you talked to her about this?”

[Mike Drop.]

# # #

(Props to Martin Cooke for teaching me the eleven words.)

How to Train Your VP of Sales to Think About the Forecast

Imagine a board meeting.

Director:  What’s the forecast for new ARR this quarter?

Sales VP:  $4.3M, with a best case of $5.0M.

Director:  So what’s the most likely outcome?

Sales VP:  $4.3M.

Director:  What are you really going to do?  (The classic noob trap question.)

Sales VP:  I think we can come in North of that.

Director:  What’s the worst case?

Sales VP:  $3.5M.

Director:  What are the odds of coming in at or above the forecast? 

Sales VP:  I always make my forecast.

Director:   What do you mean by worst case?

Sales VP:  You know, well, if the stars align in a bad way – a lot of stuff would have to go wrong – but if that happened, then we could end up at $3.5M.

Director:  So, let’s say a 10% chance of being at/below the worst case?

Sales VP:  I’d say more like 5%.

Director:  What do you mean by best case?

Sales VP:  Well, if we really struck it rich and everything lined up just the way I wanted, that would be best case.

Director:  You mean if all the deals came in — so best case basically equals pipeline?

Sales VP:  No, that never happens, I’ve made about 10 scenarios of different deal closing combinations and in 2 of them I can get to the best case.

You see the problem?  Does it sound familiar?  Do you realize how much time we spend talking in board meetings about “forecast,” “best case,” and “worst case” without every discussing what we mean by those terms?

Do you see how this is compounded by the sales VP’s natural, intuitive view of the outcomes?  Do you see the obvious mathematical contradictions?  “I always make my forecast” says it’s a 100% number, but then the VP says it’s the “most likely” number which implies 50%.  Then the VP says there’s a 5% chance of coming in at/less than worst case (which is much lower) and then kind of implies that there’s a 20% chance of beating best case – but the 2 out of 10 is meaningless because it’s not a probability, it’s just a count of scenarios.  Nothing adds up.

The result is, if you’re not careful, the board ends up counting angels on pinheads.  What can we do to fix this?  It’s simple:  teach (and if need be, force) your sales VP to think probabilistically.  Ask him/her how often:

  • It is reasonable to miss the forecast.  A typical answer might be 10%.
  • It is likely to come in at/below the worst case? Typical answer, 5%.
  • It is likely to meet/beat the best case? Typical answer, 20%.

So, with those three questions, we’ve now established that we want the sales VP to give us:

  • A 90% number on being at/above the forecast
  • A 20% number on being at/above the best case
  • A 5% number on being at/below the worst case

Put differently, when the sales VP decides what number to forecast that they should be thinking:

  • I should come in under my forecast once every 2.5 years (10 quarters).
  • I should hit/beat the best case about once every 5 quarters (a bit less than once a year).
  • I should come in/under the worst case once every 20 quarters (once every 5 years, or for most minds, basically never).

The beauty here is that when you work at a company a long time you can get enough quarters under your belt, to start really seeing how you’re doing relative to these frequencies.  What’s more, by converting the probabilities into frequencies (e.g., once every 10 quarters) you make it more intuitive for the sales VP and the organization to think this way.

In addition, you have a basis for conversations like this one which, among other things, is about overconfidence:

CEO:  You need to work on your forecasting.

Sales VP:  You know it’s hard out there, very competitive, and we don’t have much deal flow.  Back when I was at { Salesforce | Oracle | SAP }, I was much better at forecasting because we had more volume.

CEO:  But we agreed your forecast should be a 90% number and you’ve missed it 2 out of the past 4 quarters.

Sales VP:  Yes, but as I’ve said it’s tough to forecast in this market.

CEO:  Then forecast a lower number so you can beat it 90% of the time.  I’m asking you for a 90% number and empirically you’re giving me a 50% number. 

Sales VP:  OK.

CEO:  Plus, when those two big deals slipped last quarter you didn’t drop your forecast, why?

Sales VP:  Because where I grew up, you don’t cut the forecast.  You try like crazy to hold it.  Do you know the morale problems it causes when I cut the forecast – especially if it’s below plan? So, yes, when those two deals slipped it added more risk to the forecast – and I told you and the board that — but I didn’t cut forecast, no. 

CEO:  But “adding risk” here is meaningless.  In reality, “adding risk” means it’s not a 90% number anymore.  You’ve taken what was a 90% number and it’s now more like a 60% or 70% number.  So I want you to forget what they taught you growing up in sales and always – every week – give me a number that based on all available information you are 90% sure you can beat.  If that means dropping the forecast so be it.

sales forecast

This also helps with the board and the inevitable sandbagger issue.  In my experience (and with a bit of exaggeration) you always seem to be in one of two situations:  (1) intermittently missing plan and in trouble or (2) consistently making plan and a “sandbagger” – it feels like there’s nothing in between.

Well, if you establish with the board that your company forecast is a 90% number it means you are supposed to beat it 9 times out of 10 so you can only really be labelled a sandbagger when you’re 15 for 15 or 20 for 20.  It also reminds them that you’re supposed to arrive at the forecast so that you miss once every 10 quarters so they shouldn’t freak out if once every 2.5 years if that happens — it’s supposed to happen in this system.  (Just don’t let a once-in-ten-quarter event happen twice in a row.)

I like this quantitative basis for sales forecasting and I carry it down to the salesrep and pipeline level.  I believe that each “forecast category” should have a probability associated with it.  For example, at the opportunity level, you should link probabilities to categories, such as:

  • Commit = 90%
  • Forecast = 70%
  • Upside = 30%

This, in turn, means that over time, a given salesrep should close 90% of their committed deals, 70% of their forecast deals, and 30% of their upside.  Deviations from this over time indicate that the rep is mis-categorizing the deals because the probability should be the basis for the forecast category assignment [1].

Finally, I do believe that salesreps should give quarterly forecasts [2] that reflect their sense for how things will come in given all the odd things that can happen to deals (e.g., size changes, acceleration, slippage).  I believe those forecasts should be a 70% number because the sales manager will be managing across a  portfolio of them and while there is little room for a company to miss at the VP of Sales level, there is more room for and more variance in performance across salesreps.

While I know this will not necessarily come naturally to all sales VPs — and some may push-back hard — this is a simple, practical, and rigorous way to think about the forecast.

# # #

[1] Some people do this through an independent (orthogonal) field in the CRM system called probability.  I think that’s unnecessary because in my mind forecast category should effectively equal probability and your options for picking a probability should be bucketed.  No one can say a deal is 43% vs. 52% and forecast category doesn’t indicate some probability of closing, then … what use is it and on what basis should you classify something as forecast vs. upside?

[2] Some people believe that only managers should make forecasts, but I believe both reps and managers should forecast for two reasons:  (1) provided it’s left independent and not “managed” by the managers, the aggregated salesrep-level forecast provides another, Wisdom of Crowds-y, view into the sales forecast and (2) it’s never too early to teach salesreps how to forecast which is best learned through the experience of trial and error over many quarters.