Back in 2014, Hilti’s corporate payment processes were set up and managed locally. With the introduction of SAP ByDesign in some countries for the first time, end-to-end payment processing from the ERP systems to the banks became a clear need. On top of the connectivity, payment process standardization at the global level was also a priority, for compliance, efficiency, and transparency. Corporate Treasury was asked to look for a dedicated payments solution.

In 2017, Uniper decided to further optimize and standardize its payment processes. About 300 bank accounts were already managed with a payment solution, but it could not meet Uniper’s growing needs. The rest of Uniper’s bank accounts were still being managed via a range of e-banking tools, which required a lot of manual effort and hindered visibility of the company-wide cash positions. To change that, Uniper introduced the cloud-based payments platform by TIS (Treasury Intelligence Solutions), to set a company-wide standard for payment processes. Since then, data can be stored centrally, facilitating collaboration within the company, and allowing for better control and transparency over the company-wide finances and processes.

Since their founding in 2005, ContourGlobal has experienced rapid growth across all facets of their energy and power generation business. ContourGlobal’s operations quickly expanded to include power plants across Europe and eventually North and South America, as well as Africa. However, the pace and breadth of ContourGlobal’s expansion has not come without its fair share of challenges – particularly within the financial realm. As ContourGlobal has scaled over time, they have developed a large number of bank relationships and underlying account structures. By 2021, Maarten Himpe, VP of Group Treasury at ContourGlobal, and his treasury team oversaw a global network of 60 bank partners and over 800 individual accounts. The channel used to connect with these banks was SWIFT FIN and FileAct. Due to frequent acquisitions and new project launches, the Treasury team was attempting to maintain visibility to financial operations across nearly 140 unique entities. And given that treasury oversaw some thousands of payments each month across this web of accounts and entities while also controlling a variety of loan and debt agreements, cash pooling structures, and miscellaneous FX and risk-related functions, ContourGlobal’s disparate technology landscape posed a challenge. As a whole, few of their back-office systems or bank platforms were integrated with one another, which resulted in labour-intensive and potentially error-prone manual payments and reporting workflows. And without straight-through-processing of data or information between their systems, treasury’s time to focus on payment processing and cash reporting was limited. Although a TMS had been adopted to help automate certain workflows, ContourGlobal’s complex bank connectivity and payments workflows clearly required more specialized care. A solution that could sit between ContourGlobal’s TMS and their bank landscape to streamline payment processing and subsequent balance reporting workflows was needed. Ideally, connectivity to ContourGlobal’s other back-office platforms could be integrated with this new system as well, thus providing critical automation and time savings not only for treasury but the entire organization. With only 9 months available to implement a solution before the full go-live of their new TMS, there was immense pressure on treasury to move quickly. Given their limited timeframe, it was a crucial issue for the Treasury team that in addition to selecting a system with high-touch connectivity and payments capabilities, the vendor they chose would also need to provide extensive implementation and configuration support if ContourGlobal was to connect their entire banking and back-office systems to this solution before the impending TMS go-live.

Dawn Foods faced several challenges, including a lack of focus on cash and working capital, shortfalls in reporting, and a complex data landscape. The company struggled with a shortfall in management communication between departments, which hindered their ability to make informed financial decisions. Additionally, the complex data landscape made it difficult to gain a clear understanding of their cash positions and working capital needs. These issues collectively created a significant barrier to achieving their financial goals and optimizing their working capital.

Previously, many Treasury functions of MAN Energy Solutions had been handled centrally by a parent company. A carve-out posed an opportunity to establish Treasury processes that would fit the organization. One of the biggest challenges with the carve-out was to find a suitable payment solution to have maximum transparency. It was difficult to consolidate the data coming in via individual e-banking solutions, and managing them would be tied to a lot of effort from our part. MAN Energy Solutions needed a solution to avoid a large number of stand-alone systems and thus required one standardized payment platform. A further requirement was that the solution needed to be able to integrate well with MAN Energy Solutions’ ERP systems (SAP) and the newly adopted Treasury Management System (corima by COPS). Another issue that needed to be addressed was connecting international affiliates. With the carve-out as a deadline, an ambitious timeline was set for roll-out.

Kellogg’s treasury aimed to significantly improve its cash visibility, forecasting efficiency, and accuracy. The existing process was time-consuming, involving extensive work in Excel and downloads from multiple systems. Additionally, they sought to gain insights into working capital drivers to streamline order-to-cash and procure-to-pay processes. Another objective was to use FX transaction data at the invoice level to develop a daily currency hedging position, with a long-term goal of creating an 18-month rolling hedge program.

ManpowerGroup faced significant challenges in managing its global treasury operations due to a lack of integrated financial technology. The company relied heavily on manual processes, Excel, and bank portals, which resulted in limited visibility and control over cash positions, payments, and bank relationships. The use of over 150 banks and 1,200 bank accounts, with less than 25% daily visibility at the HQ level, further complicated the situation. This lack of integration and connectivity made it difficult to calculate daily cash positions, monitor payments activity, and manage the enterprise cash pool. The delays in receiving cash balances and payments data from local subsidiaries hindered short-term forecasting and cash management, obstructing the ability to pool and repatriate cash effectively.

Pearson faced a highly complex and globally dispersed financial data environment. With IT already heavily focused on digitising the business, the treasury department was keen to ensure that the workload for IT was kept low. The company needed a solution that could integrate seamlessly with their existing systems, automate data input to reduce manual work, and provide detailed insights into cash flow drivers to drive behavioural change.

Siemens Gamesa Renewable Energy faced a complex and heterogeneous system landscape due to a simultaneous carve-out of Siemens Wind Power and a merger with Gamesa Eolica. The Treasury department had to manage two different system maturity stages, with Finavigate being used for Payments, In-house Banking, and Intercompany Clearing (ICC) on the Siemens side, and a disparate, low-maturity system landscape on the Gamesa side. This resulted in a lack of harmonization, automation, visibility, and secure processes. Additionally, the merger contract ruled out the option of implementing Finavigate across all entities, necessitating a new solution. Siemens Gamesa also aimed to build a new In-house Bank based on the latest SAP version, including SAP APM, within a tight timeline to avoid penalty fees.

TomTom faced two core treasury challenges: the need for regular reporting and monitoring to gather insightful information for decision-making and financial analysis, and the issue of disparate data scattered across 125 bank accounts within 56 different entities globally. These challenges made their existing processes very manual and time-consuming, necessitating a more efficient solution.

Unilever faced significant challenges in their global cash forecasting workflows due to the complexity of their business environment. The existing process was cumbersome, slow, and involved a lot of manual work, leading to inconsistent and inaccurate forecasts. The company needed a solution to aggregate and analyze data from various sources, including banks and ERP systems, in an automated way. They aimed to achieve centralized cash flow forecasting, clear workflows, cost savings, better visibility to cash balances, and continuous improvement of forecast accuracy. Additionally, Unilever wanted a future-proof solution that was easy to implement, scalable, and provided a broad range of connectivity options.

1build faced significant challenges with their financial modeling and analysis processes. They relied on fractional CFO and accounting services, which took two weeks to create requested models. These models often lacked accuracy because third parties were not embedded in the business and did not have all the necessary information. By the time the models were delivered, the company had often moved on to new questions. Additionally, 1build was not in a position to hire a full-time finance professional, necessitating a tool that could handle complex modeling needs and provide quick answers to ad hoc questions. The tool needed to be accessible to the Head of Business Operations, Head of Operations, and CEO, who were jointly managing financial responsibilities.

Board meetings are a chance to review company performance, measure KPIs and set strategy. They are vital for addressing issues affecting growth and help bring the future of a company to light. In turn, they also require weeks of preparation pulling together and analyzing information from different departments often through lengthy cycles and disconnected data. Gem’s hypergrowth trajectory meant that sales, finance, and the board needed to be in sync often so the business could continue to scale quickly. The challenge was making sure the effort to keep everyone in sync didn’t derail their focus. Every quarter, Gem’s finance and sales org (like so many others) would lock down in a war room for two weeks to prepare their board materials. While critical to their success, this process became a repetitive, time-consuming task, stealing focus and capacity away from forward-looking initiatives to help the business grow. Gem needed a way to generate faster insights to reduce the time it took to create board materials. They also wanted a way to come out of the board meeting with fewer questions and more on-the-spot answers not possible via spreadsheets, so they could absorb the strategic value of live feedback.

For early-stage startups, finding and keeping customers (traction) and building cash flow momentum (growth) are the two most important goals. However, founders often put less effort into maintaining accurate, complete, and comprehensive data across their back-end business systems. This not only burdens the finance team with a large manual effort each month but also adds unnecessary friction as founders search for insights that can drive opportunities and better engagement with their Board of Directors. Patrick Hoogendijk, Managing Partner at Blue Phi Capital, recalls his main gripe with portfolio companies was the lack of timely and accurate information transfer, especially with financial information. As an outsourced CFO for startups, he works to eliminate that issue by building a repeatable, scalable process for communicating with founders, executives, Boards, and future investors so that each gets what they want, when they want it. Historically, Patrick would begin with data hygiene, spending weeks wrangling the data from disparate ERP, CRM, and HRIS data sources to ensure trustworthy metric calculations. He would then find a common system to communicate the business metrics to each of the startup’s stakeholders, often using Excel or Google Sheets.

Forecast OpEx and workforce investments at the speed of business growth. It’s easy for early finance hires at hyper growth companies to get locked into the role of data wrangler and spreadsheet manager. They end up spending so much time trying to keep last month’s, quarter’s, and year’s actuals organized that there’s little time left to focus on more strategic, forward-looking efforts. Tony Le and the small finance team at Pipe wanted to avoid that stereotype from the very start. Pipe launched publicly in June 2020, making its rapid rise to $316 million raised and $2 billion valuation almost unheard of in the tech world. That’s great for generating excitement among customers and investors—but it puts significant pressure on traditional finance workflows. Le and his early finance team couldn’t afford to spend days or weeks building models to plan out the business only to watch them go stale a week later. They wanted to embrace a more tech-forward approach to finance that enabled real-time visibility into the data and more dynamic, agile planning processes. The team wanted to start by modernizing its expense and headcount modeling to help ensure Pipe was properly allocating capital as it quickly scaled. They needed a software solution that could bypass traditional excel modeling while also helping them continue building a culture of strategic finance.

Emerge has been building its advanced digital freight marketplace platform and growing its business into a driving force in transportation procurement since 2017. In 2022, its marketplace surpassed $6 billion in transportation transactions, with over 1,000 shippers engaging with more than 45,000 carriers. That success propelled Emerge to realize substantial revenue growth and helped it raise $130 million in Series B funding in late 2021. But the following year saw the global macroeconomic economy start to slow, and Emerge had to move from hypergrowth to smart growth. To do so, it needed more visibility for its finance team. Emerge had migrated from QuickBooks to NetSuite, but it still needed a way to visualize business and financial performance without spending hours in Excel. And with salaries accounting for most of the company’s spend, Decker wanted to analyze its Paylocity HRIS data along with financial and other business data.

As Enboarder’s business started scaling, their small-but-mighty finance team needed to build a modern tech stack to keep up. The company was growing fast but needed to watch spending. Investing in the right tools would create efficiencies and avoid the need to hire expensive new headcount. Zhou, VP of Finance, was responsible for tracking financial performance, building budgets and forecasts, and reporting for three different legal entities. Manual work was preventing the team from providing strategic decision support. Zhou sought a Strategic Finance Platform to complement NetSuite and other existing systems.

Forage, a global business with offices in the United States, UK, and Australia, faced challenges in consolidating their global financial insights. They had to maintain multiple versions of the accounting software Xero, creating two separate sets of books and records. Operating in different countries added complexity due to foreign currency conversions, forcing the finance team to spend lengthy cycles downloading, translating, and converting numbers into standard reporting packages. As the team performed deeper analysis into customer revenue, company spend, and profit margins, it became clear they needed a more automated and streamlined reporting structure to centralize their global financial data and accelerate P&L creation. The ultimate goal was to connect the dots between key financial datasets to obtain a more holistic view of their business quickly.

After raising $50M at their Series C, Sourcegraph was looking for a faster way to analyze cash flow and expenses to strategically manage investments aligned to the company's long-term growth goals. As the company was growing quickly, the finance team needed visibility into spend by department and category as well as an understanding of the inflows and outflows of cash that impacted their burn. The company typically only looked at those metrics on a quarterly basis. But after completing their Series B and Series C, they had multiple new investors and stakeholders on board and needed the information to be visible in real-time. Sourcegraph is a fully remote company, and their accounting function is outsourced—both of which made it difficult to get real-time data in a meaningful format within stakeholder deadlines. With revenue, expense, and headcount data all in different systems, the finance team struggled to get accurate, consolidated, real-time insight into the financial indicators that mattered most. Tasked with creating a long-term growth plan while maintaining a firm grasp on current performance, Sourcegraph’s finance team wanted a faster way to analyze expense trends and predict the burn rate based on aggressive hiring plans and R&D investment.

Relying on Spreadsheets Ate Up Precious Time and Money. Like every startup, Galley runs a lean operation that moves quickly. Recognizing new opportunities and swiftly making the right moves are key to the company’s success, which relies on getting financial, sales, and other metrics into the hands of decision-makers without delay. Galley was using a bunch of spreadsheets to track KPIs, which was time-consuming and labor-intensive. Additionally, they had to manually clean customer data every month due to not keeping up with their CRM data after contracts were signed. To keep up, Galley employed an outside service to maintain its spreadsheet models and dashboards each month, adding additional overhead costs and resulting in complex spreadsheets that became too labor-intensive to update internally. Galley started searching for a new financial analytics and modeling solution that would reduce their reliance on the outside firm and complex spreadsheets. They needed a solution that could automatically pull in data from various sources like HubSpot CRM, QuickBooks, and Stripe to get real-time financial insights.

Analyzing a Rapidly Expanding Product Line\nIt’s easier than ever for businesses to diversify their product lines through software as a service (SaaS) subscriptions. The results can be great—but they need to be measured. This is especially true for teams like Revenue.io that have aggressive product expansion strategies.\nAs Revenue.io expanded from a single-point solution to a platform over the course of two years, they laid out a clear roadmap to optimize new customer acquisition. They onboarded new customers to their primary RingDNA product while methodically cross-selling other emerging product lines. Quickly analyzing new business pipelines while assessing opportunities to attach existing cohorts to other products became increasingly complex.\nFinance leaders could pull customer and deal information from Salesforce to run the necessary analyses. But, given their SaaS model, it often required up to 12 separate reports just to get a trended view of ARR. Collecting this financial information was too time-consuming, forcing the team to eventually revert to Excel to calculate the 30+ business-critical metrics they needed.\nFor Revenue.io to fulfill its acquire and expand strategy, it needed a reliable system to do two things: first, centralize Salesforce data for financial analysis. Second, turn all that data into actionable, SaaS-optimized insights for sales and product leaders.

In 2020, Canvas tripled its revenue and headcount. As they scaled ARR, they knew they would come face to face with additional investment opportunities where a rigorous outline of their financial foundation and plans for growth would be tested. Preparing for investor funding meetings is hard. It’s the round where rubber meets the road, where the promise and hope from Series A has to be met with numbers and projections that support milestones rooted in financial fundamentals. The process requires meticulous planning, multi-scenario analysis, and accurate business metrics that instill investor confidence. The Canvas team needed a way to deliver their compelling growth narrative to investors. To succeed, they needed to run end-to-end financial planning quickly and accurately. This included building pro-forma financial statements, modeling complex scenarios around headcount, understanding the ROI on their sales and marketing spend, and the subsequent effect on CAC. They also needed a way to quickly package financial insights into fundraising materials to easily communicate their growth story.

In 2021, Operations and Finance Lead Joel Blachman faced significant challenges in managing accounting, FP&A, and business operations workflows. During the Series A fundraising process, Joel spent countless hours perfecting a comprehensive SaaS metrics dashboard in Excel, which required continuous updates. This manual process was time-consuming and prone to inaccuracies, making it difficult to provide timely information to the CEO and prospective investors. Additionally, the financial planning process was impacted due to the IoT component with inventory costs, necessitating accurate balance sheet planning.

As a startup in high-growth mode, Qwick faced significant challenges in managing their financial operations. Their financial modeling was being done in Google Sheets, relying on high-level assumptions and requiring data from multiple disconnected systems like Quickbooks, Salesforce, ADP, and Divvy. This manual approach led to several major problems, including a week-long process to prepare board financials, extensive time spent on fundraising diligence, and the inability to update key metrics like CAC and LTV more frequently than quarterly. Additionally, their revenue and cash forecasts were extremely high-level, lacking the precision needed for accurate financial projections. Zack McCarty, Director of FP&A, recognized the need for a tool that could integrate all their financial data into one place to improve forecasting and build a culture of financial collaboration.

In a time when people management is more challenging than ever, Paycor wanted to equip customers with insights to bring visibility and improvement to their HR practices. Today’s world brings no shortage of challenges for HR: the labor market is tight, turnover is shattering records, millennials are job-hopping at an alarming rate, and voluntary resignations are at an all-time high. By integrating Visier into Paycor’s solution, business leaders can uncover insights into what factors are causing changes, and improve their recruitment, hiring, and HR practices. With Visier Embedded Analytics, Paycor’s customers drive more methodical decision-making throughout the organization. Now, HR leaders can spot gaps in their hiring and retention practices that impact employee turnover, while business leaders are empowered to spot trends, make informed predictions, and set reliable benchmarks.

Uber’s fast global expansion created the need for a people analytics solution to support its culture of data-based decision-making. There was limited ability for Uber’s People function or business leaders to quickly conduct analysis on their workforce, particularly across the entire organization. The company’s people data was housed in disparate systems and often categorized in different ways. This made it difficult to answer even simple questions like current headcount in an efficient, repeatable manner. Uber was faced with choosing whether to assign internal resources to build a customized people analytics solution or to select a vendor’s solution that could deliver to their requirements. Additionally, Uber’s business leaders needed comprehensive information on their people to be delivered through an attractive and intuitive interface. Time to value was also an important factor for determining their approach to a people analytics solution.

Informatica faced challenges with their existing HR system, PeopleSoft, which provided limited workforce data in a tabular format. This made it difficult and labor-intensive to generate workforce analytics, requiring significant IT time and expertise. Even after switching to Workday, the company found that the system did not meet the growing demand for strategic and predictive workforce insights. HR Business Partners struggled to have fact-based conversations with business leaders, limiting the strategic value they could deliver.

The HR reporting team at BBVA Compass was overwhelmed with data, producing numerous reports that provided minimal insights. The team aimed to shift its focus from reporting to analytics to optimize the workforce and drive business value. Their goals included reducing unwanted turnover, retaining top performers, supporting diversity initiatives, examining demographic trends, and determining the impact of training on revenue. However, the team spent most of its time collecting and validating data, leaving little time for analysis. Adding more staff was not an option.

At the start of its HR transformation, EA was using a combination of an old HRMS and a custom front end to provide transactional services to users. While the company had no shortage of data about its workforce, reports were limited and difficult to produce. To begin its journey towards data-driven workforce decision making, EA’s workforce analytics team began delivering extensive, hard-coded, monthly workforce reports to HR and business leaders, prompting both an extensive data clean-up effort and a better appreciation of HR data. Over several years, the number of complex weekly, monthly, and quarterly workforce reports that the team produced grew exponentially—encompassing a variety of trends for hiring, talent movement, terminations, demographic shifts in the workforce, and other employment factors. The workforce analytics team could not keep up with the demand for data and spent its time manually creating reports instead of building deeper analyses into underlying trends, risks, and predictive models. Building reports was a reactive exercise, and because the team lacked a flexible reporting environment, it limited its ability to slice, dice, and drill down to the right level of insight needed to move from workforce observation to diagnosis.

To take on the challenges of a fast-growing City and workforce, the City’s HR team needed to provide up-to-date workforce insights to enable fact-based decision-making. Because the City’s population is growing at an unprecedented rate, the City needs to ensure it can expand its key infrastructure and services with the right skills and talent. The City tracks data related to a wide variety of job functions—everything from garbage collection to firefighting and financial planning—so it needs to monitor workforce capacity and other critical HR topics in an efficient way. Until recently, the HR team was parsing together monthly reports with data pulled from PeopleSoft and other systems. Not only was this time consuming, but the static spreadsheets and reports did not give the City’s leadership team the ability to drill down into key issues, such as talent acquisition, worker safety, and employee retention. The HR team also needed to modernize its practices for workforce capacity planning. Once a year, they would assemble a printed binder that covered headcount by dimensions such as age, gender, and tenure, as well as the City’s wide range of job categories. This process was lengthy and because it was done on an annual basis it was out of date as soon as it was printed.