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Why CFOs should be thinking about customer onboarding

Growth for the Operational-Minded CFO Series


By Mike Psenka, CEO, Moovila


Highlights:

  1. Too many forecasting models rely on static data in a dynamic work environment (involving resourcing estimates, time to go-live, and pipeline throughput), creating revenue gaps and delaying time-to-revenue.

  2. Customer onboarding, specifically the operational plans, hold the greatest opportunities to drive growth, but only when workstreams, processes and data are connected and updated in real time.

  3. Synchronizing and monitoring processes for risk, across your entire work landscape, is nearly impossible when done manually. It’s a job for a computer.

  4. If you can “debug” a process like a programmer debugs software, you can use dynamic data for dynamic reporting, and have more accurate forecasting. You sit at the seat of real knowledge.


Everything you do in your role as CFO leads ultimately to one place: product delivery. You may rarely be involved in how the sausage is made, spending your days instead on the heady tasks of revenue forecasting, investing, budgets, and risk calculations. But your tasks are the trees in the woods. The forest you are growing is product delivery.

No one gets paid until the product is delivered.

There are no invoices, budgets, forecasts, or sales goals met/achieved until customers receive the products they ordered. There is no revenue to calculate, money to invest, or risk to take without that final transaction.

The operations data you study to build forecasts, the resource management projections you create to ensure departments are staffed without waste, and the budgets and revenue estimates you generate all feed the goal of delivering your product or service into the hands of eager (often restless) customers.

So, while it may not be your job to think about customer onboarding, produce delivery – or their guiding processes – that is where financial modeling meets operational reality.

That is also where friction, from process delays and inaccurate data, causes revenue and margin erosion. Your involvement in operational planning will influence the accuracy of predictions, analysis, and time-to-revenue.


Right now, customer onboarding and product delivery are both the enemy of financial performance, and your greatest opportunity.

It’s stifling growth:

  1. Workstream data are disjointed, quietly killing your margins

  2. The lack of process continuity feeds a cycle of reaction to putting out fires

  3. You can lead the resolution (if you care about process automation, staff retention, and growth)

But it can be a growth driver:

  1. Connected processes leads to faster time-to-revenue

  2. You spend less money delivering what you sell

  3. Customer satisfaction increases as you align expectations

 

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5 Growth Weapons for the Operational Minded CFO in 2023

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Bad data equals bad forecasts


You may not be responsible for logistics and the tactics of delivering products and services, but you go to operations with questions like “When are we going live?” or “When will this be delivered?"


You pour over sales data and staffing estimates because they are vital points in your calculations. The data you consult is almost always outdated (see why below), making your calculations just as flawed, leaving you holding the “revenue gap” bag.

The more time that passes using bad data, the more the problem (hidden to you because there’s no way to track it), balloons.



“The more time that passes using bad data,

the more the problem (hidden to you because

there’s no way to track it), balloons.”




If you issue a revenue forecast assuming a delivery date that was predicted in the product plan and didn’t know the project plan was flawed:

  • It will fail to identify work surges that put your already lean technical staff over capacity

  • Burnout will cause quiet quitting and further delays

  • Shortage of skilled workers will cause an (expensive and difficult) rush to hire

  • Cascading delays like onboarding will bleed into other projects

  • Costs spiral while revenue, reliant on operational throughput, stays stagnant


By the time the future arrives, your forecast will be embarrassingly wrong.

A better spreadsheet won’t fix this. Better task management, which is what most PSA and PM tools are today, won’t fix it either.


The only thing that will fix it is to autonomously track risk and resource capacity while


synchronizing data from all workstreams, across your entire landscape of work.

Your plans are broken


In a dynamic work environment, operational plans, break on day one.


In most project plans, you can’t run a simulation to see how the plan plays out in real time. Plans are complicated. They contain thousands of details, calculations, and fluctuating and interdependent tasks and schedules. If you make predictions about a fluctuating future from a static plan, they will not be accurate.


Software code is not published until it’s thoroughly debugged. Without that essential step, none of it would work.


Today, project plans are built that way. And they don’t work.


Scaled out, no human can scan every factor that goes into a portfolio of interdependent projects and tasks, just like no human can possibly scan every line that goes into a complex software build.

If change is constant, and projects change at the start, then what we need is a way to continuously monitor all the details across a portfolio of projects, schedules, and data points; a way to check the math.


Today, your options are limited to looking at plans and believing them to be true representations of how the project will play out. You simply don’t have enough data to do anything else. But that plan could be anywhere from zero to one hundred percent true at any moment.




“… your options are limited to looking at plans and believing them to be true representations

of how the project will play out. You simply

don’t have enough data to do anything else.”



I have seen estimates claim that 60 to 98 percent of all project plans are flawed. By my estimate, all project plans are broken, which is why projects fail well over half the time. So, before you can give up your spreadsheets, querying, and estimating, you need a plan you can trust.

You need to monitor your initial plan, with mathematical precision, so you can adjust to changes as they occur.


The opportunity: tapping into live data


What if your plan could be shared with everyone and connected to everything – calendars, spreadsheets, other product plans, human resources, operations, and sales. When you need sales or staffing numbers, those are connected and feeding everything relevant to product delivery into that plan. When something changes – in anything connected to the process – the plan knows, and adjusts, immediately.

Having this level of transparency into operations improves processes, execution time, revenue, and customer satisfaction.



“Some estimates claim that 60 to 98 percent

of all project plans are flawed…By my estimate,

all project plans are broken.”



Most plans are monitored and updated manually. That is an impossible task to ask of a person, however skilled. The fact that half of projects don’t fail is a testament to the skill of these managers.


That’s not a job for a human. It’s a job for a computer.


Unlike those project managers, however skilled, a computer can run constant calculations, monitor hundreds of schedules and spreadsheets, and track resource capacities across a portfolio of projects. It can also show you in a glanceable dashboard the current status of all those calculations and data feeds.




“You can have real-time, near-time analytics

and computation of all that data every day,

every time you log in.”




You can have real time analytics and computation of all that data every day, every time you log in. You don’t have to ask the data warehouse team or the analytics team to do big downloads, run reports, and process data separately and offline. You can look at it every day, many times a day, and it will be up-to-the-minute accurate every time you do.


How it feels to work with math instead of magic


Your financial modeling is missing a piece – a number you need to accurately forecast.


If you had that piece, you could more accurately forecast pipeline and revenue, and spot patterns and processes that are at risk.


You could grow.


If you were able to look at any project or operational plan and gauge its viability on a visual meter, you would know at a glance if you could base your predictions on that plan or if (and where exactly) you need to take action to bring the plan back to health.

For an example of what it is like to consult a debugged project plan with this kind of constant monitoring, let’s take another look at resource management.


As you forecast, you notice that the sales department posted an impressive quantity of closed projects and wonder if that means you need to budget for additional staff. And, if so, how much staff? When? And at what level?


Based on today’s seat-of-the-pants calculations, you can’t accurately know the answer to that question. so you might build in a budget for freelancers, delays, and waste.


With a plan that’s updated constantly by an AI that can do an unlimited number of calculations and never has to go home to rest, you sit at the seat of real knowledge. There is no need to guess – or pad your estimates for uncertainty. You hire exactly who you need to hire, at the right time, based on a more accurate pipeline outlook.




“With a plan that’s updated constantly by an AI that can do an unlimited number of calculations and never has to go home to rest, you sit at the seat of real knowledge.



See the truth, and play with it


What happens if you move people from project to project. How about if you add bodies? What if you change the timing of deliverables?


What if you could play around with scenarios and see what happened to all the projects in your portfolio, all the way down the production cycles. That way you could visualize when and where you need people, how many, and what skills they need to have.

Having this level of accurate information and data insight – well before you need to hire those people – is precisely what you need to create accurate forecasts. Because the less predictive your information, the worse your forecast.




"The less predictive your information,

the worse your forecast."




When you release your forecast or budget, you can’t also issue a caveat saying that the data you used to create it was old or that there were so many holes in the project plan that you can’t place faith in it. You can only say, “Here’s our forecast. Here’s our level of confidence with it.”


Operations may not be in your wheelhouse. In reality, though, you are already dealing with the consequences of flawed plans. If you have to accept that broken plans will lead to bad forecasts, budget disasters, and failures at product delivery, why not demand a better plan – one that has an oracle you can consult for truth?


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Mike Psenka is the CEO and founder of Moovila, the leading AI work management platform that uses automation and a discreet math engine to give organizations the real-time answers needed to ensure success.


 

FEATURED

5 Growth Weapons for the Operational Minded CFO in 2023


Download to learn 5 ways you can achieve operational excellence in 2023.


















 

Read the rest of the posts in the Growth for the Operational-Minded CFO Series:


How to prevent project plans from killing your profits





This one rule of probability is why your finance predictions are wrong


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