Forecasting stands as a pivotal function that allows businesses to maintain competitiveness, expand their market share and execute long-term strategies. Regardless of a company’s size, one of management’s central responsibilities involves evaluating the overall health of the business and addressing crucial inquiries: Is the company profitable or incurring losses? Can we manage our debts as they become due? Is our growth aligned with industry and market conditions?

Answering these questions relies on well-crafted forecasts developed by the internal management team, requiring a process that analyzes both internal and external data, converts it into meaningful projections and makes decisions that steer the company’s trajectory. However, the value of forecasts diminishes without accuracy. Precise short-term forecasts are essential for informed decisions, while inaccuracies can lead to severe consequences like misallocated resources, missed opportunities, financial instability and compromised strategic planning.

Drawing from more than two decades of experience in corporate finance, much of which was devoted to refining processes for generating precise forecasts, I’ve distilled key insights that have not only elevated forecasting accuracy, but also saved substantial time and effort along the way.

1. Start with Evaluating Data Quality

“Garbage in, garbage out” underscores the significance of accurate and clean financial records as the bedrock of reliable forecasts. Ensuring all revenue, cost, capital expenditure and related transactions are promptly recorded in accordance with GAAP standards is crucial. Special attention is needed, particularly for revenue transactions, often the most substantial figures on the income statement. Situations involving non-intuitive revenue recognition rules—common in software, SaaS, contract-based, real estate and certain manufacturing industries—call for scrutiny to ensure accurate recording. Robust internal controls and monthly reconciliations are essential for maintaining precise financial reporting and accounting for all system transactions.

2. Understand Key Business Drivers

Much like accurate financial records rely on competent accounting following clear processes, insightful forecasting demands Finance to grasp financial reporting and the underlying metrics. This entails understanding revenue generation, primary sales components and seasonal trends. For major expenses like labor and production, sensitivity to input prices, shifts, hours and automation is crucial. Coupled with a strong grasp of company drivers, industry insights provide context for a comprehensive understanding.

These insights, combined with the core principles of accurate data, effective data management and a robust forecasting model, form the foundation of precise forecasting practices, empowering businesses to navigate the market effectively.

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3. Effectively Manage and Utilize Data

Maintaining clean and accurate business data is at the core of this step. The accuracy of forecasts directly depends on the quality of the data that drives them. This requires a meticulous commitment to ensuring data integrity. Leveraging key data sources like ERP systems, operational data, industry benchmarks and competitor analyses will form a robust foundation. These sources not only inform forecasts, but also provide vital insights for navigating the competitive landscape. By prioritizing data integrity and effectively utilizing available information, businesses can enhance their forecasting capabilities and make well-informed decisions.

4. Construct a Robust Forecasting Model

With a foundation established through accurate historical reporting and an understanding of key business drivers, the next step involves constructing a forecasting model. While an Excel-based model is a conventional choice, alternative approaches that offer greater efficiency could also be considered. Regardless of the chosen software or method, the model should hinge on essential assumptions (or drivers) that underpin financial projections. For instance, sales revenue could be contingent on units sold, subscriptions, contracts, customers or other relevant metrics that shape revenue generation. Additional pertinent assumptions might involve average order values, product/service mix, and incorporating price and cost adjustments based on the latest consensus (pertaining to cost-of-living adjustments and merit-based increases for internal labor costs).

Integrating assumptions into your forecast actually results in more accurate projections, as comparisons between what transpired versus what was expected to occur can be reviewed and any deviations between the two can be reduced through refining the assumptions. This flexibility to rapidly reflect changes in assumptions and quantify the impact will help to significantly increase the accuracy of the modeling over time.

Conclusion

In summary, honing accurate forecasts isn’t just about getting around in the market; it’s about setting a clear path forward. Our dive into these details underscores the importance of having precise data, understanding what really drives the business, managing data effectively and building a strong forecasting model. By embracing these principles, businesses give their management sharper tools to make smart decisions, strengthen their base, fuel growth and significantly improve the accuracy of their forecasts.

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The process of selecting and implementing any system can be difficult at best and a complete failure at worst. We know from experience that many companies make avoidable mistakes in regards to new systems, such as delegating the implementation process to internal employees, avoiding formality or not planning for post go-live support. If you’d like to explore the support we offer, then visit our financial systems consulting page and start a conversation. Our free guide below also offers insight into the process of system implementations:

Let’s say you’ve recognized your current processes are slow and can’t possibly scale alongside the company’s massive growth, so you’ve decided to explore FP&A systems. You know a couple household names (e.g., Hyperion, TM1), are aware of recent additions (e.g., Planful, Adaptive), and have heard tell of new options (e.g., DataRails, Cube) popping up within the last few years.

Given the range of options, narrowing the field and selecting a system can seem like a daunting task. But many finance professionals use very common criteria when selecting a system, including reporting functionality, forecasting capabilities, collaboration workflows and more. Let’s focus on a couple of important, but less common, key factors you should consider when evaluating your next FP&A system.  

Growth Profile: How will the company grow over the next few years?

Selecting a system with the flexibility to scale alongside your company is a key factor to consider. When the company grows, acquires companies or creates new revenue streams, the needs will change, and the system will need to adapt accordingly. 

It’d be a mistake to implement a new system today that doesn’t align with company growth, only to start a new system selection and implementation process in two to three years’ time. To avoid this, think of scenarios that have resulted in significant changes to your existing models and processes and determine how a system would deal with those items.

For example, here are some scenarios to consider:  

• If your company will likely hit $1B, $10B or $50B in revenue in the next several years, does your vendor have customers in those ranges? Understanding the customers they service is a good proxy to understand their ability to service your requirements.
• If you added a brand-new revenue stream or changed an existing one, can the system handle that?
• Are you expanding into additional countries with new reporting requirements/FX translation?  

Don’t Boil the Ocean: What are our key deliverables, and how can we keep the focus on them?

When exploring a new FP&A system, many companies fall prey to feature frenzy. Demos and dialog can widen to cover the 100 items on the to-do or would-be-nice lists, when the primary focus should be on how well the system accomplishes the three to five highest-priority items. Most FP&A systems have similar functionality, so it becomes imperative that your selected system meets your most-critical needs. For example, if your company is still figuring out its revenue streams and KPIs, understanding the system’s flexibility becomes paramount. If your company is more stable, then generating reporting/dashboards quickly might be the focus. Whatever your priorities are, focus on them and how well the respective systems address those items.  
 
Here are some ideas of items that might be key priorities: 

• Expense Forecasting – Is there zero-based budgeting, per HC forecasting, applying growth rates to prior year, etc.?  
• Scenario Planning – How easy is it to spin up different scenarios or produce what-if analysis?  
• Revenue Planning – What is the functionality around sensitivity analysis, seasonality, assumption changes, etc.  
• Dashboards – How easy are they to create, update, distribute? Are dashboards a huge requirement? How self-service are they? What functionality is there? How do dashboards show data that doesn’t have a common key between datasets?  
• Collaboration/Workflow Capabilities – How well does the system handle tracking workflows, document sharing, commenting, etc.?  
• Company Industry – Does the vendor have functionality focused on a certain industry (e.g., SaaS)? This may be an advantage of one vendor if they have built in functionality for that industry, but it may be a disadvantage if you’re not in that industry. If the vendor has numerous of your competitors as customers, then it may be a good sign that they have the functionality you require. 

Ease of Use: How easy is it to learn the system, and is there ample availability of resources with hands-on experience? 

Every system will have some sort of learning curve, but issues can arise when staff inevitably turn over, lowering internal knowledge to support the system. Focusing on how easy it is for people to learn the system can help avoid those issues. While some systems can be figured out by digging around, others may require the help of external consultants to help troubleshoot. Here’s a list of ideas to test the ease of use:  

• Can a typical finance professional poke around and figure out most of the functionality?  
• How easy is it to create reports? 
• How easy is it to input data into the various templates/models?
• How easy is it to create/modify the Revenue and Operating Expense models?
• Does the syntax used in the system mirror Excel’s? (Because all finance professionals are Excel pros, the more similar the syntax, the better.)

For each of these items, think of the curveballs that you’ve experienced in your current process, how you’ve had to modify existing files/processes and ask how the system would deal with it. You’re looking for relative ease in making similar adjustments.  

If the system isn’t particularly easy to use, then the other consideration is whether the system is widely used enough that ample finance professionals with hands-on experience are easy to find. While not as critical in a system that is easy to use, a large user base becomes more of a consideration for systems that are more complicated. That allows you to find someone who can slot in and manage the system without much issue.

Additionally, if you’re planning to roll out the system to BU partners, then you’ll want to understand their use cases and see whether it is easy for them to use. Can they easily navigate through reporting/dashboards? Can they create their own easily?  

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Data Cleanliness: How clean is your data?  

In order to unlock the full power of FP&A systems, you need to be able to intake data from a variety of sources across your organization. You’ll want to take stock of all the data sources (e.g., GL system, CRM, BI tools, databases) you want to bring into your FP&A system and understand whether the system has native integrations or would require custom integrations. Then you must understand your underlying data structure to determine what it looks like, if it has all the fields you care about and if data cleanup is required. If you’re constantly undergoing data cleanups, changing KPIs, modifying hierarchies, etc., how will the system accommodate that? Some systems require that your data be clean at the source while other systems will allow you to use logic to modify the data as you see fit.

Once you’re done with that, you’ll likely need to do some data cleaning, but if you’re constantly undergoing data cleanups, changing KPIs, modifying hierarchies, etc., then you’ll want to seek out a system that is flexible enough to deal with those situations. 

Some FP&A systems work best when the data is stable and changes are relatively minor, but not all can deal with messy data. 

Where You Work: Do you want users to work primarily in Excel/Google Sheets, or do you want to work in a system?

There are two schools of thought around this question. One school is centered around the belief that you will be the most efficient when you transition work from Excel to a centralized system. The other school believes nothing will ever replace the flexibility that Excel/Google sheets provides.

While many systems offer plugins to also do work in Excel, only a handful of systems are built with Excel/Google Sheets as the primary UI (e.g., DataRails, Cube, Vena). Of course, you should expect natural differences in systems that were built with Excel/Google Sheets in mind and those that added that functionality over the top.  

It is up to you to determine what you think makes the most sense and how you want your team to operate. When it comes time to decide which approach makes sense, go back to your pain points and see which can handle them better. For example, if you have a ton of data, can these Excel/Google Sheets-based tools handle it quickly and efficiently?

Online Community: How can you ask questions, find answers and suggest improvements? 

The more robust the system’s community is, the more resources that will be available to quickly troubleshoot issues and collaborate on functionality you want to explore and implement. These communities become places where other finance professionals share their struggles, and many members share their solutions. Additionally, the communities often function as a way for the vendor to gather ideas and eventually implement them into the system. It’s quite common for a given community to vote on desired functionality and for software companies to roll out that functionality over time.

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The process of selecting and implementing any system can be difficult at best and a complete failure at worst. We know from experience that many companies make avoidable mistakes in regards to new systems, such as delegating the implementation process to internal employees, avoiding formality or not planning for post go-live support. If you’d like to learn more about the support we offer, then visit our financial systems consulting page and start a conversation. If you’d like to learn more about systems implementations, then download our free guide below:

Power BI is an extremely powerful data transformation and reporting tool with solid modeling capabilities via tools such as DAX and Python/Panadas. Besides connecting a litany of Microsoft products (e.g., SQL Server, Azure, SharePoint, Excel), it can also connect to many other data sources including Salesforce, Anaplan, Postgres, Oracle and SAP. This in-house ability to access diverse data sources puts a strong tool in the analyst’s tool kit. The ability to access, transform and visualize large amounts of data does present some important best practices for long-term success. In this article, let’s review a few Power BI tips that can help you leverage the tool effectively.

Optimize Your Data Warehousing

The first of our Power BI tips is the actual condition of the “data warehouse,” whether it be a relational, multi-dimensional or other data structure (e.g., Big Data). To optimize Power BI, the data at the source should be cleansed, transformed and consolidated as much as possible in the source system. This doesn’t necessarily mean every table or cube should be perfect, but they should be in the best shape possible.

This optimization may translate into building special tables, objects or views in the source that result in cleaned, consolidated and transformed data. The importance of this cannot be understated: cleaning and transforming large data sets can slow and even stop Power BI processing.

Build Common Data Tables and Structures

The second of our Power BI tips would be moving Power BI calculations that occur in multiple dashboards, reports or datasets into a common data table or structure. These calculations should then be accessed in one location by all Power BI resources—versus each resource running the calculation(s) locally.

This effort will free up Power BI computing resources, making page loads faster and, more importantly, ensuring that all Power BI resources are using the same formula. Often when the same formula is used across multiple Power BI resources, changes in one are not always carried over to all resources using the formulas. Also, considerable time can be spent managing formulas across resources. Moving the formulas to a common data structure eliminates these issues.

Identify Necessary Data Granularity

With the ability to work with large amounts of data, one challenge that occurs is pulling only on the amount of data required versus everything available. Power BI resources can be overcome with too much data which results in slow performance and even the resource “freezing.”

Which brings up our third Power BI tip: One way to manage the amount of data pulled into a resource is to determine the correct amount of granularity required to support a visual. For example, if a visual requires analysis on a low level of granularity (e.g., daily), can that analysis be performed in the data warehouse and the Power BI resource pull only required elements? Another option is to create aggregated data tables/Objects in the source by omitting columns not required by the Power BI resource.

Implement an Oversight Process

Last tip: When a company has many Power BI resources (e.g., Dashboards, Reports, Data sets) in production, it is important to have an oversight process. This ensures consistency across Dashboards and Reports—both in terms of data and presentation when needed. For example, the process would ensure similar formulas are properly managed across resources.

An Oversight Process also helps manage the resource landscape by minimizing the occurrence of duplicate resources, supporting future development, and simplifying general management of the Power BI landscape (e.g., Security, Development Flow, etc.). Setting up a process can be implemented by having periodic meetings which include Power BI resource developers, project managers and data warehouse engineers and cover the current and future reporting landscape and how the data warehouse/sources play a role.

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Employing these Power BI tips will result in more streamlined resources that run faster, are easier to manage and can provide better insight into the data analyzed. That noted, many companies don’t have the internal bandwidth to implement these best practices. If you’d like support on your data transformation and reporting efforts, then consider contacting us. Our Accounting and Finance consulting team can deploy to support or drive key projects or serve in an interim management capacity if needed.

If you’d like to learn more about generating internal momentum for operational objectives, then you might be interested in our guide:

In part one, we explored best practices for empowering cost-center transparency in your QuickBooks to NetSuite migration. Those recommendations and the exploration below come from my experience in supporting a company through that process. As an FP&A professional, I found the migration exciting due to the advanced reporting and analysis that was available in the new platform.

The QuickBooks to NetSuite migration commonly occurs when a company seeks aggressive growth and advanced efficiency in its finance and accounting functions. In our case, it allowed for enhanced reporting, budgeting and forecasting.

SG&A – Allocations & Headcount

In QuickBooks, the allocations split in terms of projects SOWs (i.e., revenue) and expenses (i.e., resource cost) was done manually. In terms of headcount, various employees were allocated to multiple cost centers. This was inefficient and created a lot of room for potential errors.

Due to the approach to allocations and headcount in QuickBooks, our Scorecard was not always accurate. The cost center owners frequently disputed the numbers from finance, as these numbers affected the perceived performance of their departments. But often, the disputes were centered on inaccurate or imperfect data. Because various people worked on projects across more than one cost center, in some cases, the true expense didn’t match the revenue. As a result, finance had to frequently make manual changes to make the Scorecard more accurate.

We worked with our NetSuite implementation team to ensure we would correctly allocate employees working across cost centers. We leveraged the time entry function to empower everyone to track their time in a way that accurately reflected cost center expenses. After the QuickBooks to NetSuite migration, the allocations split directly mirrored an employee’s timecard for that week, down to the project level.

For example, people working in both the R&D and Technology cost centers had their time split in NetSuite according to their respective, current projects. This level of granularity generated a truly accurate Scorecard—and for the first time, cost center profitability was completely transparent and accurate. The biggest rewards from this time entry function in NetSuite were removing unnecessary disputes and giving the cost center owners more confidence in the finance team and the integrity of our work.

Additionally, every employee in the company needed to have a home cost center, even if their allocation for the month was split. HR housed everyone’s designated cost center and the allocations in NetSuite aligned with the direction from HR.

Reporting, Finance Model Flow & Forecasting Accuracy After the QuickBooks to NetSuite Migration

QuickBooks is great for a smaller-sized business. However, for a medium-sized business looking to grow, NetSuite supports scale by creating more automation and efficiencies in data quality, report creation and day-to-day transactions such as JEs, AP, AR and PO workflow approvals.

In terms of financial analysis and forecasting, we pursued the QuickBooks to NetSuite migration to better analyze and monitor issues that affected profitability, growth and productivity. We achieved this by creating cost center hierarchies as well as other various dimensions in the data in terms of revenue and expenses. We also wanted to clearly identify trends and developments in sales and costs to improve forecast accuracy.

Feeding NetSuite Data Into Our Forecast Model

For organizations that have many subsidiaries as mine did, NetSuite allows a consolidated view of the financials at any given point in time, and it allows you to drill down to specific subsidiaries or other dimensions as needed. This helped us better align our Sales and Finance forecasting models to identify key drivers and identifying root causes of previous discrepancies.

For our forecast model, the data out of NetSuite was much more refined than when it was in QuickBooks. Using a NetSuite financial report, we cleansed the data and made sure it contained all the dimensions (fields) and measures we wanted to see. We used Excel for our forecast, so the way we updated our financial forecast model was by taking an extract of that NetSuite report. It was easy to copy and paste this data into our Excel model in the data tab inputs, and the output pages by cost center would automatically refresh.

As we actualized months, our forecast became an extrapolation of the actuals depending on run-rate or trend, and it became easier to create the remainder of the year forecast. We could then layer on any one-time events or uptick in revenues as needed. We could do this with expenses as well—build a run-rate forecast then layer in any expected additional expenses.

We were also able to actualize our live forecast based on where we were in the year in terms of actuals. So, if we had six months of actuals and six months of forecast, we then had a true, live, actualized 12-month forecast. This enabled us to see where the hits and misses were and also better informed us if we needed to update the forecast.

I have also previously worked at companies who fed NetSuite actuals directly into cloud-based systems such as Hyperion Essbase or Workday Adaptive Planning. In that case, if you had a live 12-month forecast in Hyperion Essbase and six months of actuals (e.g., January – June) in NetSuite, these actuals and six months of forecast (e.g., July – December) would reflect “6+6,” or six months of actuals and six months of forecast. The actuals serve to inform the direction of the forecast, so utilizing NetSuite with a cloud-based system is very useful. The actuals give you insight into trends occurring through historical data, which will give you the baseline assumptions for your forecast. You can then layer in larger, one-time events into your forecast as long as you’re clear on what your baseline is.

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Custom Reports and Month-End Efficiency

NetSuite also allows users to create unique reports by adding various columns and rows of relevant data. For the Income Statement at month-end close, FP&A was able to pull together a detailed report that gave us a good preliminary snapshot of what month-end close would look like at the cost-center level. From this, we were able to determine if there were any erroneous or missing JEs.

When the income statement was final at the end of the month, the raw data was then copied into our finance model (which was actualized by month). We would consider the model refreshed, and then the numbers would flow into our month-end, Excel-based financials, which also served as the basis for our final month-end decks.

The finance model contained all of the MTD and YTD budget and forecast information. Once finalized actuals were populated into the model, it was easy to see where the variances were.

I also created a financial scorecard by cost center, and we held a monthly meeting with the C-level audience. Thanks to the data quality in NetSuite, we were able to feed this newly refined data into our Excel-based Scorecard and track MTD & YTD results accurately. This Scorecard tracked revenue and gross margin dollars so that profitability by cost center could be determined—and annual bonuses could be paid to GMs based on actual results.

Get Support for Your QuickBooks to NetSuite Migration

While I’ve focused on the specifics I experienced while supporting a company through a QuickBooks to NetSuite migration, the fact is that transitioning between financial systems and optimizing their effectiveness are dependent on your organization’s goals and your approach to them. If you suspect you need supplemental support or would like a dedicated project manager to spur and maintain progress, we invite you to contact us to start a conversation.

And if you missed the first part of this series, make sure to check it out to explore how to increase cost center transparency when moving from QuickBooks to NetSuite. You can also keep up with our team of finance and accounting consultants by subscribing to our CFO insights blog. For help with your financial systems, visit our service page to learn how we work with our clients:

I once joined an organization as its migration from QuickBooks to NetSuite was just being finalized. As the needs of our business grew and became more complex, so too did our need to migrate our financials to a more efficient, functional ERP. We were also looking to restructure the basic P&L view from very high level (i.e., revenue, COGS, direct and indirect expenses) to a detailed view (i.e., via cost centers) so that General Managers and VPs could take more accountability for the financial performance of their departments. For the month-end close and some of our transactional processes, we wanted a system that offered more flexibility and functionality. 

The organization had acquired seven smaller business over several years. In terms of functionality and future system needs (specifically potential outputs and reporting), this needed to be thoroughly laid out to maximize the efficiency of NetSuite. Also, we wanted to ensure there would be an ROI through a combination of process improvements, which would create more transparency to see where we could leverage and/or reduce costs.

Based on that experience, let’s go over some recommendations for how you can successfully increase cost center transparency in your move from QuickBooks to NetSuite.

Before moving from QuickBooks to NetSuite, have a formal discussion with the C-level audience and key stakeholders about desired hierarchy and organizational structure.

We held recurring meetings with key company stakeholders and the CFO, CEO and VP of Operations to discuss what the new organization hierarchy structure would look like. The CEO decided that there would be seven revenue cost centers and six SG&A cost centers in NetSuite. He identified the names of each cost center and the cost center owners, and then we created unique cost center IDs in NetSuite per his direction.

The discussion with the C-level audience was important as the cost center owners and other C-level people live and die by the success of their business. Also, the salary and bonus structures of VPs and GMs per their prior-year performance were based on whether or not they achieved their minimum given goals and/or if they exceeded their goals.

For the business to scale, we needed to clearly outline the benefit of NetSuite’s functionality and how it would augment their future financial performance. It was made very clear to the C-level team that to migrate to NetSuite was a win/win for everyone.

Creating the cost center hierarchies in NetSuite eventually allowed us to see both revenue (KPIs) and all pertinent expenses in the newly modified data in NetSuite. This type of transparency was never visible in detail in QuickBooks. NetSuite, the new ERP, also would create more accountability in terms of tracking key KPIs and expenses by cost center.

Clean your data, test your setup and recognize that part of moving from QuickBooks to NetSuite will be sunsetting old habits.

The legacy QuickBooks data wasn’t properly scrubbed and did not contain cost center or product family hierarchies. The data needed to be cleansed as part of this migration process. Once the agreed-upon balances were achieved, the period ending balances were transferred from QuickBooks, and they became the beginning balances in NetSuite. In addition to the balance transfers, all vendors and customers were also moved over into NetSuite.

For the new chart of accounts (COA) developed, we had to ensure both QuickBooks balance sheet accounts as well as QuickBooks P&L accounts were properly mapped (reconciled) into NetSuite and that nothing was missed. We also had to create new unique account descriptions and account strings and vendor/customer IDs to ensure no duplicates were being captured or created.

The income statements and balance sheets in QuickBooks were standard, consolidated (i.e., total company), high-level P&Ls. We had to align each part of these financial statements into NetSuite and assign a project manager from the accounting team to oversee the technical aspect of this process. We had 12 global subsidiaries (entities) that were part of our global consolidation, so we had to ensure that each subsidiary was correctly migrated into NetSuite and that these subsidiaries also a part of our final global consolidation. A full test was required once this was set up in order to ensure all entities were rolling in correctly in both local currency and USD.

It’s important to note that the cleaning and restructuring of data involved the understanding that YOY balance would not be apples-to-apples analysis. As noted earlier, we wanted to show these financials at the cost-center level for further transparency. The QuickBooks data was not structured by cost center or product family, which made YOY balance analysis complicated in terms of organic comparisons vs. the data in NetSuite. Additionally, legacy vendor and customer info was also structured differently.

Accounts Receivable (i.e., customer name) and Accounts Payable (i.e., vendor name) needed to be sorted through and cleansed to prepare for testing and streamlining in the new environment. All vendor names and customer names had to be consistent, with no duplicates or variations of the names.

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You cannot overestimate change management, training and the magnitude of the mind shift in moving from QuickBooks to NetSuite.

A huge pitfall in my experience was that the accounting team wasn’t keen on change, and they weren’t properly trained for this seismic shift. Properly coding recurring and non-recurring journal entries and invoices in Accounts Payable to a new chart of accounts with a new accounting string was something that wasn’t fully explained to the accounting staff. The lack of proper, prior training on how to code journal entries and invoices ended up creating more work for higher-level accountants to reclassify items. It also creates variances for FP&A professionals trying to analyze month-end actuals against budget.

This meant more training after the fact. At the origination of journal entries (JEs) for month-end close, all accountants were trained on how to:

1. Code properly per the new chart of accounts,
2. Use the correct cost center account string, and
3. Add a consistent brief description of the JE as a reference line.

This training not only improved our data as it was inputted in the system, it also helped in the timing schedule given for month-end close. We were able to shorten the close window from 60 days post-close to 45 days.

The redesign of our financials, both balance sheet and income statement, were in the standard format of NetSuite reports. These reports allowed the ability to drill down.

In our Excel-based Global Revenue file (KPI tracker) we layered in the new cost center names and product family categories into the data. We had three main lines of business that these KPIs were captured under, so this info also had to be layered in as well.

Training for FP&A team members is also important due to the various reports that NetSuite has the functionality to create. It’s quite useful for an FP&A person to figure out how to pull a report together, either at the cost-center or line-item level (e.g., revenue, OpEx, etc.) for proper month-end analysis against budget and forecast. One can certainly be creative in NetSuite in developing, from scratch, a report with all of the things you want to see. For example, I created a new NetSuite report that was at the cost-center level, and the process involved creating columns and aligning data rows correctly to successfully develop this FP&A income statement.

The mind shift that needed to occur for the Finance and Accounting teams one of immersion, training and testing. We needed to fully be trained and acquainted with relevant NetSuite features and capabilities, and we needed to be empowered to try novel approaches. If we didn’t immerse ourselves fully into leveraging NetSuite as its own system—and instead tried to make it operate like QuickBooks—the migration effort wouldn’t have fully served its purpose.

Even the cost center owners had to immerse themselves into NetSuite to understand how to approve Purchase Orders, create and approve invoices, track time and get the most out of the newer workflows in NetSuite.

All other employees, such as those in R&D and SaaS cost centers, needed to get acquainted with the timekeeping system and ensure their billed time was correctly allocated to the right projects. They also had to learn how to make sure that they were billing their time correctly to respective cost centers.

Give your team a realistic timeline, appropriate resources and time to test.

We acknowledged early that our in-house team did not have the bandwidth to handle their day-to-day duties and take on implementation tasks. We hired a third-party NetSuite implementation team to assist us with identifying the inefficiencies or the limitations of our processes in QuickBooks. That helped us to determine what could be improved in our move to NetSuite. Many system implementations can be halted by not having enough resources to carry various tasks through, but our NetSuite consultants helped speed up the sandbox testing process along at this stage.

At this stage, we made sure every possible transaction scenario was tested in our sandbox prior to any possible modifications, and our NetSuite consultants were on hand for any issues we encountered.

We met on a weekly basis with the NetSuite consultant team, and we created a timeline with various tasks assigned to different consultants. It was important to have this status meeting to know if there are any hiccups that would prevent us from not achieving certain milestones in our timeline.

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Empower users through project setup training, workflows and appropriate permissions in NetSuite.

In terms of Accounts Payable (AP), we utilized Concur, which directly interfaced via cost center with NetSuite so that various reimbursements for employees would be appropriately paid with their payroll. We sought to make the AP transition as seamless as possible by automating our Procure-to-Pay process with all appropriate controls in place. Our AP Manager played a big role in leading this process with the NetSuite consultants.

For Accounts Receivable, we sought to ensure customer invoices were automatically generated once a project was completed in NetSuite. Once a project was marked as complete, it would act as a trigger in NetSuite to create an invoice. We also double-confirmed all net payment terms with our customers to be sure NetSuite reflected the same net terms and that our AR balances did not go into past-due status.

When creating a project or SOW in NetSuite, it was important that the setup was 100% accurate from the start; otherwise, it would cause problems later. Employee project setup training is a must to sure proper revenue recognition and that billing/invoicing is flowing through the correct business line and cost center.

We assigned only two or three people as superusers of NetSuite. The rest of the employees (e.g., cost center owners) in other departments such as Legal, HR, Marketing and IT were considered regular users. These superusers (i.e., Controller, Director of Systems, CFO) had full permissions and could also grant or deny certain types of access to various users across the organization. (The superusers would only grant certain access if there was a business need and proper managerial approval.)

We designed PO process workflows in NetSuite at the cost-center level, so that only cost center owners had the ability to approve their own POs. Each cost center owner was assigned as an “approver” of POs for their respective cost center and was able to create POs and customer invoices. Certain direct reports to cost center owners, depending on their level, were also assigned advanced permissions to create POs and customer invoices. The spend threshold was limited for the cost center owners, and if the threshold amount was considered high, approvals would need to be automatically routed to the CFO, and in some cases, the CEO.

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Stay tuned for part two, in which we’ll explore recommendations for enhancing budgeting, reporting and forecasting after your QuickBooks to NetSuite migration. You can also subscribe to CFO Insights to receive email notifications when our team publishes new articles.

If you’d like to learn more, you can visit our related service page to learn more about our financial systems consulting services. You can also download our guide below to learn more about the phases of ERP implementations:

The adage “your analysis is as good as your data” is more relevant today than ever before. Technology has enabled us to record and store more data than we can conceivably process. With the increase in the volume of data, one needs a powerful system that can help define, categorize and report on that data seamlessly. This need has led to the emergence of the multidimensional database platform.

The majority of any finance and accounting resource’s time should be spent in data analysis as opposed to data management. But still, managing your data is integral to producing meaningful and impactful analyses.

At a high level, a multidimensional database allows the user to define and categorize the organization’s data into different “dimensions” or “viewpoints.” (For example, a customer account might possess different dimensions such as name, location, account type, etc.) A multidimensional database would tag a customer account with the dimensions listed above and then create different “dimensionality lists,” where you could view your entire customer portfolio categorized into the dimensions listed above (e.g., name, location, account type, etc.). The multidimensional database builds on this key functionality to produce curated automated reports/analyses on demand.

Popular platforms include Microsoft Analysis Services, Oracle Essbase and Cognos Analytics. It is important to note that these platforms are not just smart databases. They also possesses the ability to perform complex calculations and build analytical reports similar to a Business Intelligence (BI) tool.

Who Needs a Multidimensional Database Platform?

Most organizations are using Excel to store large data sets and run resource-heavy calculations and processes. At a high level, if your current data and reporting infrastructure leads to the challenges below, your organization needs an multidimensional database platform:

• Volume of data exceeds current system capabilities and application performance
• Manual processes lead to inefficient use of organization’s headcount and are prone to errors
• Lack of a centralized data repository, leading to data inaccuracy
• Challenges with version management and access control
• Lack of robust management reporting capabilities
• Systems and databases that are not integrated and require manual data migration

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What Are the Benefits of a Multidimensional Database Platform?

A multidimensional database platform would offer a range of increased functionality and efficiencies.

Scalability/Data Storage to Support Company Growth

These platforms offer the ability to quickly ingest additional data sets and storage capability without compromising on accuracy or system speed.

User-Friendly GUI That is Customizable to Client Needs

Multidimensional database platforms are extremely user friendly with easy-to-use user interfaces. The user does not have to be an advanced programmer as the GUIs typically allow for simple “drag and drop” functionality allowing for ad-hoc reports to be built on the fly.

Open API Platform for Data Connectivity

These platforms tend to be system agnostic and are open-ended in nature. A good multidimensional database platform can seamlessly integrate with other databases or BI tools.

Access Control (e.g., Admin, Read/Write user, Read users)

The user has absolute access control over the platform. Different access levels can be granted to individuals or organization groups.

Version Control

This function provides the ability to immediately roll back to prior versions. This is an important function especially during the budgeting process, where a budget typically goes through multiple scenarios and versions. Version control also helps the user perform several “what-if scenarios” when forecasting or performing ad-hoc analyses.

Application Performance/Availability With Intricate Calculation Engine

This offers the ability to compute calculations across large data sets that are seamlessly integrated on the back end. The back-end connectivity results in extremely fast performance with minimal system lag.

Ad-hoc Reporting

These platforms offer the ability to drag/drop metrics and attributes for instantaneous reports (similar to Pivot Tables). A non-specialized user can easily create reports in an instant using a drag/drop feature that is standard with all multidimensional database platforms. This negates the need to request the Fintech (Finance Tech) team to create, test and release new reports. The end user has absolute control over the report creation.

Dashboard Reports

Users have the ability to build automated dashboards for KPI reporting (e.g., Sales Performance Metrics, Pipeline Reporting, Executive dashboards). The user can also create reports and perform a data refresh on a chosen timeline (weekly, monthly etc.). These platforms also provide the ability to email dashboards to select recipients, manually or automatically after the initial setup.

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An efficient multidimensional database platform provides an enterprise-wide system to synchronize your strategy and execution, allowing all your business functions to work in synergy towards achieving the organization’s goals. The collaborative environment, enterprise-level reporting capability, real-time reporting, automated report creation along with other key functionalities make these platforms not a “nice-to-have” but a “must-have” for some organizations in today’s business environment.

If you want support on financial system selection, implementation or optimization in your organization, we invite you to explore our services. Our team of 90+ finance and accounting Consultants can help in a project execution or interim management capacity.