Global study finds AI use rising in finance, but skills gaps and trust concerns remain widespread

Over the past decade, companies have invested heavily in data visualization. Power BI, Tableau, and their equivalents are now standard issue across the enterprise. And yet the promise of better decisions hasn’t fully materialized. Not because leadership teams aren’t capable, but because the tools have outpaced the data foundations they depend on. “Companies have spent 10 to 15 years building out visualization tools, but what most of them haven’t done is prioritize proper data organization as part of their corporate DNA,” says Matthew Gantner, Founder and CEO of Altum Strategy Group. “The dashboards look good. The underlying data isn’t structured to give leaders what they actually need.” The issue isn’t the display layer. It’s everything underneath it — data quality, data velocity, KPI relevance, and the organizational discipline to act on what the numbers are saying. Until those foundations are in place, dashboards risk becoming investments that haven’t yet reached their full potential. The partial insight trap Brendan, Client Delivery Manager at Altum Strategy Group, sees the same pattern from the implementation side. Companies default to standard metrics — utilization percentages, headcount ratios, basic financial summaries — often before the contextual modules that make those numbers meaningful have had a […]

Introduction In a high-volume, high-velocity, low-margin business, the finance function cannot afford to be slow. Every day the books stay open is a day leadership is flying without instruments. For a growing restaurant distribution company, that was the reality. Their accounting and operational systems had not kept pace with the business, and the gap was being filled by something no CFO wants to depend on: human heroics and Excel. Altum Strategy Group was brought in to change that — and over three years, we did. The Challenge The company had grown significantly, but its financial infrastructure had not grown with it. Reporting relied on manual effort across fragmented, siloed systems; at least ten separate applications that could not talk to each other and could not provide the unified view that leadership needed to run the business. Getting a clear picture of financial health required considerable manual intervention every reporting cycle. The consequences were predictable. The monthly close took 30+ days. Operational visibility was inconsistent. Headcount planning across locations was difficult to execute with confidence. Leadership could not easily identify where operations were overperforming, where they were underperforming, or where attention was most needed. The finance function was consuming capacity that […]

For decades, finance teams have measured efficiency by how quickly they could process invoices, reconcile accounts, and close the books. Artificial intelligence is accelerating those tasks dramatically, but according to Altum Strategy Group’s Brendan Polke, that isn’t the most important story. The real opportunity isn’t simply automating accounts payable or accounts receivable. It’s giving finance professionals the time and information they need to create more value for the business. Organizations that approach AI solely as a cost-cutting exercise risk missing its greatest potential. The companies seeing the strongest results are using automation to eliminate repetitive work while allowing finance teams to focus on analysis, oversight, and strategic decision-making. Polke says, “Think of AI as a value-creating opportunity rather than a cost-cutting initiative. It’s a new way to run your financial operations, not simply a way to replace the old one.” Efficiency Is Only the Beginning Much of today’s discussion around AI focuses on speed. Finance teams can process invoices faster, automate data entry, generate reports, and reduce manual errors. These gains are significant, but they’re only the first step. Once organizations are no longer consumed by repetitive administrative work, they can begin asking bigger questions. Why are we paying for […]

Organizations have never had more visibility into their operations. Dashboards track revenue, utilization, customer activity, inventory and workforce performance. Executive teams can access more information, more quickly, than at any point in history. And yet a lot of organizations still struggle to make confident decisions. The problem isn’t a shortage of data. It’s knowing what to do with it. Most companies are reasonably good at measuring performance. Far fewer have figured out how to turn those measurements into foresight, meaning the ability to see where the business is heading before the trend is already in the rearview mirror. As investment in analytics platforms and reporting tools has grown, one thing is becoming clear: dashboards don’t create better decisions on their own. They create visibility. What organizations actually do with that visibility is a different question entirely. Dashboards Provide Signals, Not Answers One of the most persistent misconceptions in performance management is that more dashboards mean better decision-making. It doesn’t. In practice, designing dashboards well is as much an art as a science, and the dashboards that actually serve leaders are built for context, not just metrics. A high-performing employee might show low utilization simply because they complete work faster than […]

For many mid-market companies, data governance becomes a priority only after growth starts exposing operational cracks that can no longer be ignored. Reporting takes too long to reconcile. Different departments produce different versions of the same number. Teams spend more time manipulating spreadsheets than analyzing performance. Executives begin questioning where the data came from instead of what it actually means. At first, organizations work around the friction. Finance teams manually adjust reports before leadership reviews them. Operational teams build tracking systems outside official platforms. Employees create workarounds because the business still needs to move. But eventually growth exposes the underlying problem. According to Brendan Polke, Manager at Altum Strategy Group, the issue is rarely a lack of data. He says, “The data exists, but it’s usually fractured between departments and systems.” This fragmentation increasingly becomes a business issue rather than simply a technical one. As organizations scale, disconnected data environments create operational inefficiencies, slow decision-making and limit the company’s ability to use reporting, forecasting and AI effectively. When Systems Stop Speaking the Same Language Within companies, disconnected systems, implemented at different stages of growth, are rarely fully aligned. Sales forecasting sits inside the CRM. Financial reporting lives in accounting software. […]