Experts in ICM: Reaching Data Nirvana with Rachel Parrinello & Isaac Hausman

In our Experts in ICM Series, we sit down with leaders from across the incentive compensation and sales performance management space to explore learnings, trends and opportunities that exist for today’s ICM and SPM professionals.

We most recently spoke with Alexander Group’s Rachel Parrinello, principal and sales compensation leader, and Isaac Hausman, principal and data science leader. 

In this conversation, we discuss the pain go-to-market (GTM) teams experience during sales planning. Across many organizations, we’re seeing “planning whiplash,” with leaders scrambling through spreadsheets, making fast decisions without the right data and often working in silos.

In the face of these challenges, our experts share how to reduce fragmentation, lean into flexibility and optimize sales plans with confidence.

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As we think about challenges with sales planning, one recurring theme is fragmentation. Different teams often build their own models, update numbers on their own timelines or rely on siloed data sets. The result is that quotas, territories, incentives and capacity plans can quickly drift out of sync. 

How does this kind of fragmentation typically show up across the planning cycle?

Isaac Hausman: As the data science guy, I skew a little bit more towards the segmentation, capacity planning, territory and quota side of things.

In terms of fragmentation, it's having data nobody believes in, the lack of it or those components being disconnected. It's really making sure that there is clean alignment from both a data and a process perspective so that those things are working in concert. 

Two other examples of fragmented planning that I've seen:

1. A planning team updated the entire segmentation methodology with a complex kind of opportunity model, something that your average rep wouldn't understand out of the box. This was used to redraw territories, creating massive field disruption. I think upwards of 40 to 50% of the accounts changed hands in that exercise.

Because that original segmentation work was not explained to the field, they really didn't understand why they were being reassigned territories and what led to that logic. That company was forced to undo some of those changes mid-year, essentially due to mass revolt. This points to the importance of communication and making sure that the components of the process are talking to each other.

2. Another example is not understanding the opportunity in each territory. Oftentimes, we see the same quota or growth goal being added to every single territory when there are massive differences in the opportunities available in each one. 

Sometimes it’s making sure segmentation is talking to territory design, but it's also layering in other sources of information that can actually bring people together around a unified view to drive a good market opportunity map. 

When planning happens in silos, it doesn’t just create operational headaches. It directly impacts sellers. How have you seen fragmentation erode trust, create confusion or even drive attrition within sales teams?

Rachel Parrinello: When a seller doesn't have hope that they're going to hit their goal or that they're going to be earning market, competitive pay, they are out the door. 

[BLOCKQUOTE
| Quote: Loss of trust will lead to loss of hope.
| Author: Rachel Parrinello
]

Another example I have is with a recent client where the leaders wanted to put this new metric in the plan. The operations team didn't have a seat at the table to really say, “Yes, we can do this.” They rolled out a new measure for roughly 15,000 employees, and then ultimately had to backpedal that measure because there was so much confusion. Neither the data or dashboards were available for people to see and understand how they are doing against the measure.

When it comes to sales compensation, planning teams need to make sure that people:

1. Understand it
2. Have access to the goals they’ll be measured against
3. Have access to the data with which their attainment will be measured. 

Otherwise, again: loss of trust, loss of hope and out the door. 

Everyone has the best intentions when it comes to planning, but fragmentation still causes issues because planning is complex. How have you seen teams effectively reduce silos during sales and incentive planning?

Rachel Parrinello: First, make sure you get your governance structure in place. Identify all the key stakeholders that need to be involved. Then, outline the governance charter and solidify what each stakeholder is responsible for throughout the process.

When it comes to sales compensation, you need sales leadership, finance, HR, sales operations, RevOps and, occasionally, marketing. You’ll also bring in legal at the very end to approve the communication materials, policies, etc. 

The second thing that I think is super important to break down silos is to have a North Star. Have a set of guiding principles and goals that you're trying to reach and get alignment on the North Star from the planning committee upfront.

Then, let the design team work on the designs that align to that North Star. What you don't want to have happen is to go to your approval meeting and have the steering committee say, “No, you missed the mark. We have to start all over.”

So, it's the governance, the principles and then, thirdly, it's the data—having a single dataset that you're using and a common set of definitions.

For example, I had a client that used a term, “pay mix,” for their ratio of their base and their variable. But they also use the term “mix,” to determine the ratio of the revenue component versus the management by objectives (MBO) component. This caused confusion at every meeting. 

Isaac Hausman: In terms of typical data silos that we see, it's sales data being disconnected from market data. Another big one is not having product-level information, and that can be a direct tie in to the measures piece that Rachel was just talking about. For example, we want to accelerate sales of this new product, but we don't have a baseline sales history. And we can’t see the marketing interest or engagement around that product.

Marketing is part of these planning exercises as well, especially from a segmentation standpoint. Make sure you can connect some of the marketing and contact-level data into the sales CRM data and then create a consistent view of product across all stages of the funnel.

For example, are you able to tie a product into select marketing channel engagement? Do you have that same exact product hierarchy in your CRM from a pipeline standpoint, so that you can track the full buyer journey? Not just at a total level, but at a product level?

That’s one of the big pieces of planning information that we see missing. 

When you zoom out, it’s clear that siloed data isn’t just an operational headache, it’s often the very thing that keeps organizations from realizing the full value of their planning. 

If the end goal is alignment, transparency and confidence in the numbers, then the question becomes: How do you get from today’s fragmented reality to a world where everything is connected, consistent and trusted? How do you get to data nirvana? 

Isaac Hausman: To get to data nirvana there's a few other things that you could look at, such as bringing in additional enrichment sources (ex. intent data). And then another piece would be the post-sales side of things. Make sure that you're looking at actual product usage. So if you're in the tech space, that means customer support ticket data. That way, you’re getting that kind of end-to-end customer life cycle all connected in one place. 

These days, this is all very achievable. Tools like Snowflake bring that centralized data warehouse together. There's some other more sophisticated components in there, such as validating your contacts. Also, there's some AI tools that are good at making sure your contact lists are up to date with the most recent titles and that they still work at those companies.

What are some realistic things people can do immediately to start moving towards that data nirvana state? 

Isaac Hausman: When we’re starting from ground zero, just getting company level information de-duplicated is a good first step. That means making sure you don’t have multiple instances of the same account.

Even for many companies that are bringing together two legacy systems, parent-child hierarchy can be another one. We don't have a unified view of customers and the products that they purchase. I do caution that it can be a rabbit hole.

No one is perfect at it. There are always buying centers that are relevant to your business that are neither a global parent nor a local child but have something. Get a basic parent-child hierarchy going, so that you can factor that in from a planning perspective. Maybe some accounts need to be covered globally. Some are going to be covered more at the child level. 

From there, add in contact validation. Then, you can get to the more custom data feeds and full enrichment environment. That’s a good way to lay out the roadmap.

[BLOCKQUOTE
| Quote: The real cautionary tale there is don't try to do the “301” before the “101.”
| Author: Isaac Hausman
]

If you're trying to bring in new enrichment data sources and you don't even have your account list de-duplicated, go do the basics first and then look to bring in the additional widgets. 

Getting a trustworthy dataset together is critical to building a strong plan. But even then, so many leaders are still left asking: “Is it really working?” 

How can RevOps and incentive compensation teams help increase confidence that their plan isn’t just based on clean data, but is truly the best-optimized plan for the realities of this planning cycle?

Isaac Hausman: Yes, many plans do feel hopeful. However, there's not necessarily a blueprint or backbone that really spells out the details of said-plan. I see a lot of companies not necessarily even building that first-pass business case that gets you to the plan. I think the number one thing is tying it back to data and realistic assumptions. What accounts? What contacts? What products? How are we actually going to build up to this number that we set as the annual plan for the year? 

The second piece that's often missing from the equation is the view of opportunity. Make sure you at least have your assumptions in place about where this is going to come from. Some of those assumptions might be optimistic. You can validate some of those assumptions by doing market opportunity models, spend potential models and propensity models. These models can actually help you assess if there’s enough juice to squeeze in these products, in these markets and in these segments. 

A lot of times, folks are planning without even doing the first part. If they are, they’re not necessarily marrying it up with a view of opportunity. There are many ways to do that. You can start very basic, with linear assumptions. You can also do some of what my team does and build complex machine learning (ML) models that get at that type of information.

I know from experience that forecasting and the plan are often passed down. It's not optional. For me, while you want to have confidence in your plan, maybe even more valuable is understanding where is the plan really stretched? Then, you can decide how to mitigate it. If you don't have that view of where it's stretched—such as where you may be assuming that you’re going to capture 80% of available opportunity next year, which is likely be unrealistic—then you're not going to be able to go through that mitigation type of planning approach.

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