Workday Adaptive Planning

Multi-Site Healthcare Organizations Rely on Workday Adaptive Planning

June 28, 2024 by Revelwood

The market for the multi-site healthcare industry is booming due to population growth, aging demographics, increasing healthcare needs and advancements in medical technology. There is continuing demand for convenient and accessible healthcare services provided by these organizations, which are often funded by private equity firms or joint ventures.

One of the biggest challenges facing multi-site healthcare organizations is scaling operations. They are often faced with a breakdown between operations and general and administrative (G&A) functions. This is particularly an issue with financial planning and analysis (FP&A), which includes budgeting, planning, forecasting and reporting.

Helping these multisite healthcare organizations with their FP&A processes and technologies is one of our specialties. Our team at Revelwood has worked with many of these organizations to transform their businesses. Here are just a few examples.

Dental

One of our clients is a dental organization with more than 240+ affiliated dental practices across 15 states. The organization provides centralized management and shared G&A services. We built a specialized, custom Workday Adaptive Planning-based FP&A solution that included:

Creating a dentistry operations model with volume-based modeling between dentistry and hygiene practices
Creating an orthodontics model with 24-month uneven revenue recognition including historical revenue and actuals
Building models for patient and volume-based revenue and staffing logic
Integrating Great Plains and PowerBI with Workday Adaptive Planning

Eye Care

Another Revelwood client is a leading provider of clinically integrated eye care, with a national network of over 700 optometrists, 300 ophthalmologists and a total workforce of 6,000 people. It has more than 700 affiliated practice locations with services that span the eye care continuum in 18 states and in 30 markets.

Revelwood built a customized, multisite healthcare budgeting and forecasting application for this organization. The solution included:

Assessing the data sources and incorporating a new SAP chart of accounts (COA)
Developing a plan to extract the data, re-map it and re-load it
Building distinct models for its optometry and ophthalmology practices
Creating models to enable budgeting and forecasting across locations, including number of patients, number of exams, number of operating days, historical price and rate inflation

Urgent Care

One of our clients is a recognized leader in health system urgent care joint-ventures. It is a physician-owned, physician-driven company committed to providing convenient access to quality, cost-effective healthcare services through a retail urgent care delivery model.

Revelwood built a Workday Adaptive Planning FP&A system for the organization. The solution incorporates:

Corporate-level workforce planning for 250 full-time employees
Revenue forecasting by clinic, including per visit using historical averages, factoring in seasonality and different reimbursement rates
Comprehensive internal and external reporting, including reporting on budget versus actuals, department levels, income statements and more
An integration with Intaact

Learn more about how we are helping multi-site healthcare organizations.

Workday Adaptive Planning Tips & Tricks: Importing with Ease

June 26, 2024 by Revelwood

One of the key features of Workday Adaptive Planning is the ability to import data in mass efficiently, saving time and reducing errors. In this blog post, we will provide a step-by-step guide into the import process, providing detailed information on accessing import templates and correcting errors seamlessly within Adaptive Planning.

Understanding Import Templates for Workday Adaptive Planning

Import templates serve as structured frameworks that define the layout and formatting requirements for data uploads. These templates are essential for maintaining consistency and facilitating error-free data imports.

Accessing Import Templates

Here are the steps to access import templates in Workday Adaptive Planning.

1. Navigate to the specific sheet or module where data needs to be imported
2. Look for the “Actions” menu and select “Import Data” or a similar option
3. Choose the appropriate template based on the type of data you are importing.

In this example, we will use a simple Level import template found within Modeling > Levels

Revelwood is an award-winning, Platinum Solution Provider for Workday Adaptive Planning. We build solutions for the Office of Finance that minimize your risk by seamlessly incorporating business analytics into your everyday thinking. By combining the software with our best practices and out-of-the-box applications, we help businesses achieve their full potential with Workday Adaptive Planning.

Workday Adaptive Planning Tips & Tricks: Capital Summary Sheet – New & Existing Depreciation

May 29, 2024 by Revelwood

The capital summary sheet provides a snapshot of an organization’s capital assets and their depreciation with an overview of CapEx by asset type and level. This sheet allows the user to see the total depreciation, which is broken down by new depreciation and existing depreciation, as well as fixed assets.

New Depreciation gives us the monthly depreciation of all the new budgeted assets for the new budget period by month. This comes from the Capital sheet via a linked account to carry dimensionality.

Existing Depreciation covers assets that were acquired prior to the current planning version and are actively depreciating. This information can be taken from a depreciation schedule directly from the ERP system or imported into a separate supporting schedule within Workday Adaptive Planning.

Fixed Assets are the new assets that are purchased in the given period and the purchase value that will be capitalized and depreciated. This also comes from the Capital sheet via a linked account to carry dimensionality.

Workday Adaptive Planning Tips & Tricks: How to Filter Data for Sage Intacct Integrations within Adaptive Staging Tables

May 15, 2024 by Marc Assenza

There are many times when importing data into the staging tables for Sage Intacct integrations that I am looking for just a subset of data and not all the data. Importing everything takes time, and if you filter your retrieval in the staging area, you can save time on the import and spend that time on more impactful things.

The screenshots below show you a few ways in which you can apply some of these filters.

In Sage Intacct, the General Ledger Details table contains just that – all the details for all types of transactions, including for all time and all reporting methods.

What if you didn’t want all that data in the staging area? How could you limit it?

For starters, in this example, you would click on the down arrow icon next to the General Ledger Detail table name, and select Table Settings from the context menu presented, see below.

A screenshot of a computer

Description automatically generated

A new screen will pop up with the options you now see.

In the area labeled “Data Import Mode,” set that to All records that fall within a period range transmitted. If we look down to Period Range to import, we see that this is set to a “parameter” named CurrentYearToDate.

This parameter was created by clicking on the Edit Parameter link right under the Period Range to Import. When you click on this, you then have the option to create a Period Range parameter as seen below.

Once you click on the parameter, you have the options to define what that parameter will look like and the range it will grab, it can either be static, dynamic, or a combination of both. For this parameter, we designed it to grab two years of data from whatever the current month and year is. The Start Period is two years backwards from the ending period, which is the current month and year.

Once that is in place, you can then select that parameter as the Period Range to Import and match it up against a column in the table named Entry Date. If the data in the Entry Date column is within the date range of the defined parameter, it will be imported into the staging area table.

Two years of data is still a lot of data. In this example, we only want data that has a Reporting Method of “ACCRUAL” in the General Ledger Detail table. There are many reporting methods available within Sage. If you are only reporting on Accrual data, then you only need to import the Accrual data. As such, our filter now only imports two years of data that meet the reporting method criteria. This shaved quite a bit of time off importing this subset of data into the staging tables.

Solving Financial Reporting Challenges

May 3, 2024 by Revelwood

This is a blog post from our partner Workday, highlighting common financial reporting challenges and explaining how to solve them.

Stakeholders want self-service: Reporting runs the gamut, from presenting department managers with data on how their actuals compare to budget, to showing board members how expansions or changes in the product mix are impacting margins.

Why it matters: Businesses largely run on accurate, timely financial reports, as they are home to critical financial and operational key performance indicators.

Most organizations know that their financial reporting is not as good as it should be. The reasons are many—chief among them is the perception that process improvements are too difficult and take too much time to implement.

But when you put better reporting on the back burner, you put your business at risk. Instead of looking in the rear-view mirror—a static approach to planning that reports on what happened in the past—it’s far more effective for finance teams to look out the windshield and anticipate what’s ahead.

Let’s take a look at four common financial reporting challenges and how to tackle them:

Challenge 1: Verifying Accuracy

Excel is a great tool. But the static nature of spreadsheets makes it difficult to quickly and consistently produce up-to-date financial reports, which compromises speed and accuracy. Spreadsheets can also create version-control issues when they’re routed for review or verification, hindering efficiency and security.

Even with single-user spreadsheets, lack of a centralized reporting system introduces more inconsistencies in metrics, data, and calculations, forcing finance teams to spend valuable time verifying and validating data. In this situation, it’s especially difficult to conduct variance and comparative reporting—a step that can reveal necessary course corrections. CFOs who automate data gathering can instill a greater level of trust in the data while making it easier to reveal valuable insights.

Excel is a great tool. But the static nature of spreadsheets makes it difficult to quickly and consistently produce up-to-date financial reports, which compromises speed and accuracy.

Challenge 2: Wrestling Data from Multiple Systems

As a finance professional, you’re responsible for generating clear and actionable financial data. Your company’s decision-makers must be able to understand not only the analysis behind the data, but also the actions to consider as a result of that analysis.

But one missing piece of data can prevent stakeholders from getting the insights they need. And with more organizations tracking nonfinancial metrics, corporate reports are including increasing amounts of operational data. Using traditional reporting methods to access and incorporate such information—usually housed outside of finance—creates an additional burden.

Challenge 3: Lack of Collaboration

Financial reporting should be a collaborative process, with finance and nonfinance managers working together to not only report the numbers, but to also use them to drive insights and take action. But all too often, operating managers don’t have sufficient input or buy-in to the financial planning process, and they aren’t educated about how their decisions can influence overall profitability. For its part, finance isn’t able to offer real performance insights that might truly help managers improve their results because legacy reporting tools don’t enable stakeholder collaboration.

Challenge 4: Data Interpretation

You’ve gathered the data—now you need to analyze and interpret it so you can clearly articulate financial and operational insights. The more the organization understands the story behind the numbers, the greater the chance it has to be data-driven—and the more effective you can be in getting your message across to key stakeholders.

That’s because those outside of finance tend to consume data visually. They seek more than just numbers; they want to understand the impact and implications of the data you present. For those wanting to make good on good intentions, intuitive dashboards and data visualization are a great way to build a story that clearly shows current performance, future trends, and possible scenarios. Ideally, you should choose a dashboard offering that gives finance staff the flexibility to quickly and easily deliver data in a range of formats desired by stakeholders.

What’s the Answer?

To overcome these traditional reporting challenges, you need to go beyond yesterday’s inadequate access to information and limited financial reporting. You need a system that is more sophisticated than a spreadsheet, but not so overly engineered that it takes six months to deploy and requires significant IT involvement.

The solution you choose should deliver financial intelligence that drives improved business performance and accelerates growth. And it should enable an active planning approach to finance—a process that allows finance to shift into a leadership and guiding role, instead of having to focus on static, transactional back-office tasks.

This blog post was originally published on the Workday blog.

More from our FP&A Done Right Series:

The Promise of AI in Finance

The Role of Generative AI in Forecasting

The Future of FP&A: Intelligent Forecasting

The Role of Generative AI in Forecasting

March 22, 2024 by Revelwood

This is a blog post from our partner, Workday, highlighting findings on Generative AI from a Deloitte CFO Signals quarterly survey.

In the world of finance, Generative AI has entered the chat.

In a recent CFO Signals, Deloitte focused part of its survey on Gen AI and found that “a sizeable proportion of CFOs’ organizations (42%) are experimenting with it, while 15% are incorporating it into their business strategy.”

Nearly one-quarter (24%) of respondents said they’re “reading and talking about it,” while another 17% opined “it’s too soon to tell.”

Generative AI—the technology that can take vast amounts of data and use it to create new content—has captured the attention of a wide variety of industries.

And it’s no surprise, considering the potential impact of the technology. Last year, McKinsey & Company estimated the global economic benefits of Generative AI could add the equivalent of $2.6 to $4.4 trillion a year across 63 use cases it analyzed. As a point of comparison, the report noted that the United Kingdom’s 2021 GDP was $3.1 trillion.

A Cautious Approach Toward Gen AI

Reflecting a cautious, analytical approach as a whole, the survey’s 115 respondents expressed a few common concerns around Gen AI and the potential benefits of AI in finance.

Finance leaders’ top three concerns were around the technology: “impact to risk and internal controls” (57%), “data infrastructure and technology needs” (52%), and “investment needs (technology and capabilities)” at 51%.

The findings reflect the need for responsible AI on a wide scale to establish trust, minimize risk, and drive greater business performance.

What AI Can Do for the Finance Function

While a significant proportion of CFOs are considering the risks of an increasingly technology-enhanced future, the potential benefits of Generative AI are also dawning on them.

Almost half of finance leaders (49%) named planning, forecasting, and analysis as the top potential uses of Generative AI, far outpacing the automation of routine or transactional processes (26%) and increased efficiency (20%).

Meanwhile, CFOs identified the top three benefits they hope to achieve if their organization were to adopt Gen AI:

Reduce costs (52%)
Improve customer/client experience (50%)
Increase margins, efficiencies, and/or productivity (45%)

Other potential benefits include developing new capabilities, products, or services; creating scale and/or capacity; and improving the accuracy of forecasting, modeling, and scenario planning.

What’s Needed to Incorporate Gen AI in Finance

Lending weight to the idea that intelligent finance demands a human-centered approach to AI, a majority of CFOs (63%) said talent resources and capabilities present the biggest barrier to adopting and deploying Gen AI within their organizations.

Finance leaders further said that the single most important factor in helping them make decisions related to using Gen AI are use cases (39%). CFOs also mentioned wanting to understand the ROI of gen AI, as well understanding of risks and limitations along with best practices from peers within their industry.

While widespread adoption of AI in finance hasn’t yet happened, it’s clear that it’s on the radar of many CFOs in the forefront.

“Do they have the necessary data, technology, and talent to implement GenAI?” Deloitte wrote in its report. “The survey results suggest no―not yet anyway. But for now, CFOs appear to be curious about the upsides and downsides of GenAI, and what opportunities, as well as challenges, the technology might bring.”

Read the full CFO Signals 3Q 2023 report at Deloitte.

This blog post was originally published on the Workday blog.

More from our FP&A Done Right Series:

CFOs on AI, Partnerships and Skills

Workday’s Global CFO AI Indicator Report

The Mandate for Business Agility

Tracking KPIs for SaaS Companies

March 11, 2024 by Revelwood

High-growth SaaS companies have to be rigorous in their planning. They need to allocate resources strategically. They need to be able to quickly run different scenarios in order to understand the impact of changes to their business.

For example, you are the CFO of a SaaS business. You’d like to update headcount and ARR under contract models to reflect Q1 actuals. You need to incorporate revised pipeline forecasts from sales. What does this mean for your Q4 cash position? In the world of SaaS, this one “small” change triggers a waterfall of updates consuming hours, days or even weeks. That is time you simply do not have.

As with many businesses, SaaS companies rely on Key Performance Indicators (KPIs) to understand how the business is performing. But what KPIs should you be tracking?

10 KPIs for SaaS businesses

Here are 10 KPIs you should track:

1. Customer Churn Rate – The percentage of customers lost in a given time
2. New Buyer Growth Rate – The speed at which you gain new customers over defined periods of time
3. Lifetime Value – The revenue from a customer over the retention time period
4. Customer Acquisition Costs – The amount of money a company speeds to get a new customer
5. Net Burn Rate – The Net Cash spent in a specific time frame (usually monthly or normalized to a year)
6. Runway – The time that a startup has before they run out of finances
7. Average Revenue Per User (ARPU) – The average revenue generated per customer (either monthly or annually)
8. SaaS Quick Ratio – This compares revenue added (new business) vs revenue lost (churn)
9. Monthly Recurring Revenue (MRR) – This is the monthly revenue from customers with a subscription
10. Total Addressable Market (TAM) – The market size of a product/service in value that the company can achieve

Workday Adaptive Planning is a strategic resource to help you uses up to date data to drive your KPI models.

How SaaS Companies use Workday Adaptive Planning

Subscription waterfalls – forecast new and renewal ACV/ARR, retention and churn by segment
Sales rep productivity – plan sales rep capacity, quota coverage and territories
Cohort modeling – model subscriber cohorts, retention, lead conversion and contract ramping
Professional services – plan bookings, backlog hours, billing rates and utilization by role
606 revenue and commissions amortization – model complex revenue and commission amortization profiles based on contract duration
Workforce planning – plan and reconcile head count plans to manage a growing workforce
Vendor-level spend – budget and actualize IT, consulting, marketing and other material expenses at the vendor level

The Future of FP&A: Intelligent Forecasting

March 8, 2024 by Revelwood

This is an excerpt from a blog post from our partner Workday. It provides insights on how Generative AI will impact FP&A activities.

Digital transformation and data go hand in hand. Most executives get this: today, the vast majority view data as a critical asset to be tapped, and new AI capabilities have made this data more beneficial than ever, says Michael Schrage, a research fellow at the MIT Initiative on the Digital Economy.

But here’s the catch, Schrage asserts: Most executives can’t name the five most valuable data assets within their organization, or their firm’s return on data (ROD). That’s a problem, he says, because if a business isn’t paying close attention to the strategic value of its data, making the right AI investments will be much harder. And as the age of generative AI and machine learning (ML) takes off, the potential ROI on those investments for CFOs and financial planning and analysis (FP&A) teams is massive. Achieving those returns requires merging and marrying your most valuable data with AI.

The ways AI can power a paradigm shift in forecasting and metrics are coming into focus, Schrage says. Trained on customized data sets, large language models (LLMs) can turn KPIs into intelligent mechanisms that help create new value, instead of just tracking and protecting value. And with ML supporting FP&A activities, forecasting can become a source of dynamic insights to support operations and workforce planning—far more than just an accurate financial picture of the future. KPIs become tools for better key performance insights and key performance investments.

In other words, “The generative revolution changes everything,” Schrage says.

Future-Ready Metrics

With data now a lifeblood connecting and defining the digitally transformed organization, metrics have become increasingly important for value protection and value creation. Schrage’s most recent research focuses on combining generative AI, ML, and KPIs, asking whether KPIs can evolve beyond being simple measures and instead become software agents capable of learning.

This idea is no longer a hypothetical, given dramatic developments in generative AI over the last few years. Aided by AI, metrics can become forward-looking tools to support forecasting and scenario planning activities, helping finance leaders be more proactive and strategic.

Using ChatGPT, you can actually ask the KPI questions that matter most, Schrage says. “What could we do to improve you? Is the data helpful to you? What new data would improve your forecast? What would you say under this circumstance? Do you think this scenario would be good for you or bad for you?”

The bottom line: AI can help the finance function drive value with more predictive and future-oriented KPIs, whether it’s classic metrics such as revenue, profit, and sales, or increasingly important hybrid financial custom-facing metrics such as customer lifetime value or customer churn rate.

“What if your customer lifetime value KPI could talk to your customer churn KPI? The math of that kind of thing is interesting,” Schrage says.

Data + AI = Intelligent Forecasting

The potential value of predictive insights unlocked by AI is huge. So long as LLMs are trained on quality data—bad data is a major stumbling block for organizations in adopting AI, a global Workday survey found—finance leaders have the opportunity to rethink what forecasting can and should be.

“Is a forecast about being correct and precise, or is it about being a source of insight and conversation for how the business should prepare and prioritize, go to market, or respond to customer needs?” Schrage asks. With custom LLMs or ML in the mix, forecasting becomes a richer, more cost-effective way of gaining actionable insights for the organization.

When it comes to scenario planning, Schrage sees multiple potential forecasting use cases emerging via generative AI apps built atop customized LLMs. Expect to see emerging AI/LLM ecosystems (such as Hugging Face, LangChain, and OpenAI) allow businesses to connect data streams from platforms such as Workday with generative AI systems to populate scenarios with real data and defined parameters, he says.

“The ability to interconnect, to create interoperability between Workday and specific scenarios—it could become really meaningful, something that could be part of a compliance stress test for one’s FP&A initiatives,” Schrage adds, observing that the costs for these kinds of analytics are coming down.

Starting Points

The scope and purpose of a custom forecasting model or scenario will vary business to business, of course. But all organizations should start their AI and ML planning journey from the same place, Castonguay says.

“You have to start with your business needs,” he adds. “What problem are you solving for? Figure that out and go from there.”

Data can be another entry point, Schrage adds. “If data is an asset, then what are your most valuable assets—and how can you get greater value from them?”

Answering that question is made harder by data silos, which remain common. Nearly two-thirds (59%) of organizations report their data is somewhat or completely siloed—and just 4% say their data is fully accessible, according to the latest Workday global survey. Those numbers need to change.

To boost accessibility and value extraction in the age of AI, Schrage suggests the finance function needs to step up and take charge of data.

“For the future of capital allocation, CFOs should be first among equals,” Schrage says. “They should be the drivers of change.”

That makes sense considering that finance—once slower to adopt AI than other functions—is gearing up its AI activity. Gartner® predicts that by 2026, 80% of large finance teams will rely on internally managed and owned generative AI platforms that have been trained on their own proprietary business data.

This blog post was originally published on the Workday blog.

More from our FP&A Done Right Series:

CFOs on AI, Partnerships and Skills

Workday’s Global CFO AI Indicator Report

The Mandate for Business Agility

CFOs on AI, Partnerships and Skills

February 16, 2024 by Revelwood

This a blog post from our partner Workday, sharing thoughts from the CFOs at Kickstarter, McKinsey & Company and Workday.

It’s never been more important for CFOs to understand and embrace technologies with the potential to transform the finance function—particularly as the impact of AI becomes more apparent every day.

“If you look at the role of the CFO today, which in many ways is a core component—if not the strategic architect—of an institution, you have to look at the opportunities around technology,” said Eric Kutcher, senior partner and CFO at McKinsey & Company. “If we’re going to drive growth and productivity … technology probably becomes the number one source of that productivity.”

Finance leaders must familiarize themselves with technologies in a way that helps them not only see firsthand the possibilities for enterprise value, but also understand how younger generations have come to experience technology, Kutcher said. That’s particularly important with generative AI, he added. “It’s hard to be leading an organization of the size and scale we all do if we’re not at the forefront.”

Those were just some of the critical observations that came out of a CFO panel in a recent Fortune webinar. Read on to learn what more Kutcher, Kickstarter CFO Sindy Wilson, and Workday CFO Zane Rowe shared on their approaches to people and technology in the era of AI.

The CFO Role in Innovation

CFOs have largely fulfilled a financial controller function within organizations, protecting value by evaluating ROI. While that remains a core function for finance leaders, the future of finance is built on value creation.

That shift necessitates CFOs to think about significant enterprise expenditures on technology as investments, which requires CFOs to establish greater partnerships with CIOs and CTOs.

Part of that journey, Kutcher added, involves shifting to a mindset that asks: “How do we evolve our firm or institution to enable us to do the things that are strategically important—much of which has an innovation component to it—and how do we create the economic model to do that?”

That’s how CFOs can go from someone whose purpose appears to be cost containment to being an enabler of innovation.

Finance leaders are positioned to have a broadly informed and valuable perspective, Kutcher said. “You have this unique vantage so you can ask those questions and can invite yourself into some meetings, and as long as you do it in a way that is uplifting and moving forward.”

For his part, Kutcher said he makes telephone calls to his peers on McKinsey’s leadership team on at least a weekly basis. “I’m actually just curious what they’re doing, both personally and professionally.”

AI’s Potential: ‘The Biggest Sea Change’

When it comes to AI in finance, Kutcher said he’s bullish: “With the limited experiments we’ve already done with AI, it has created real opportunities for us to have better insight and be able to synthesize much faster.”

Kutcher added that he only expects the technology’s speed and quality to improve over time, enhancing strategic thinking and allowing for deeper questions.

“We’re just at the beginning, but I think this is the biggest sea change we will see not just in finance but in business at large.”

Why Relationships and Trust Matter

Building trust with technology leaders is important for Sindy Wilson, CFO at Kickstarter.

“Gaining an understanding of our capabilities and challenges has really helped to build trust and have less friction-filled interactions with our technology leaders as we try to solve for innovative solutions we want to develop together,” she said.

Wilson added that one of her goals for herself and her team is learning. “I want them to be a student of the functions that we support,” she said.

Finally, Wilson values transparency about how she makes decisions. “I’m an incrementalist,” she said. “I like to make sure that we test and learn. I want to pilot a kind of proof before making big investments, and the team understanding how I think about how we make investments is important as well.”

People and learning are also an important part of technology strategy for Zane Rowe, CFO at Workday.

“As CFOs you should be encouraged to work closely in partnership with technology—a practice that can help leaders identify shared opportunities, whether it’s around AI or other advances in technology,” he said.

Rowe said he spends plenty of time with colleagues on the business technology side “to think about how we do things better not only in finance but across the organization, to become more efficient and then invest in other parts of the business.”

Technology as ‘Co-Pilot’

As AI plays a larger role in finance, Rowe emphasized the importance of CFOs recognizing the technology’s capabilities.

“It’s incumbent upon you to learn and to understand it’s not necessarily learning in conventional ways,” he said. “To really understand what is the art of the possible doesn’t mean you have to become a coder. Spending enough time and being influenced by people in technology will help you understand what those opportunities are.”

Acknowledging the increase in “consumerization”—or low-code, no-code interfaces—of business technology, Kutcher said he views technology as a “co-pilot” to assist people. “At some level, it is less about understanding that technology, and more about understanding the application of that technology.”

Rowe described how that works in practice: At Workday, the finance organization conducted brainstorming sessions in partnership with the technology group to come up with ideas for real-life use cases where AI and other technologies could increase productivity and efficiency.

“It was an opportunity to have real-time results and have teams go out and try different things,” Rowe said. “The speed and the consumerization of it is really impressive.”

Using Data to Achieve Efficiencies at Scale

Wilson recounted her previous experience at a multibillion-dollar construction materials company that grew via acquisitions to more than 200 manufacturing locations. The fragmented structure of the company’s components meant multiple customer relationship management (CRM) and enterprise resource planning (ERP) systems.

“The challenging part was integrating those,” she said. “We realized we needed to get smarter about how we can leverage the power of our manufacturing footprint to improve things like on-time delivery for customers and as a go-to-market as one sales team.”

Wilson said her team worked with Kickstarter’s technology organization to conceptualize what kind of architecture, tools, and systems they needed—including ERP and CRM systems—as well as the processes they needed to put in place “to make sure we have the right policies and practices around clean data.”

The Path Forward

Kutcher also had a bright view about what AI can do with quality inputs.

“I’m actually remarkably optimistic about the path forward, in part because one of the things we are learning is: You can pull an awful lot out of existing systems and find ways to make great use out of it,” he said. “What we’re doing with generative AI already is a great demonstration of that—and, by the way, that’s only going to get better as we go.”

Rowe said the growth of AI has put pressure on companies to think more strategically about investing, as well as how to analyze data to generate insights with far greater speed than was possible before.

“It’s an exciting time to be part of finance as well as part of IT, and we both need each other just as much.”

Workday Adaptive Planning

Dental

Eye Care

Urgent Care

Understanding Import Templates for Workday Adaptive Planning

Accessing Import Templates

Read more Workday Adaptive Planning Tips & Tricks:

Read more Workday Adaptive Planning Tips & Tricks:

Read more Workday Adaptive Planning Tips & Tricks:

Challenge 1: Verifying Accuracy

Challenge 2: Wrestling Data from Multiple Systems

Challenge 3: Lack of Collaboration

Challenge 4: Data Interpretation

What’s the Answer?

More from our FP&A Done Right Series:

A Cautious Approach Toward Gen AI

What AI Can Do for the Finance Function

What’s Needed to Incorporate Gen AI in Finance

More from our FP&A Done Right Series:

10 KPIs for SaaS businesses

Read more from this series:

Future-Ready Metrics

Starting Points

More from our FP&A Done Right Series:

The CFO Role in Innovation

AI’s Potential: ‘The Biggest Sea Change’

Why Relationships and Trust Matter

Technology as ‘Co-Pilot’

Using Data to Achieve Efficiencies at Scale

The Path Forward

More from our FP&A Done Right Series:

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