Stop Looking Over the Cliff With Uncertainty - Figure Out How to Bridge That Gap By Jay David Founder - Do Business Better Author - Turnaround Revelations Every executive has experienced the moment. The management team is gathered around a conference table reviewing the monthly results. The waterfall analysis is complete. The cost model is sound. Revenue, price, mix, labor, productivity, and overhead have all been reconciled. Every variance is explained. Every bridge balance

Twelve executives approved the same profitability model. They had each signed a different one. EPM implementations don't create the misalignment between FP&A and BP&A, they expose it during the build, at the worst possible cost. Why the dimensional model is the forcing function that surfaces the disagreement your deck hid for months, and how to settle the definitions before the cube does it for you.

By Gary Cokins; Analytics-Based Performance Management LLC, President … and Profitability Analytics Center of Excellence (PACE), Director What is cost accounting? Is it simply a form of accounting for how expenses (e.g., salaries, wages, purchases) are calculated as costs (e.g., products, service-lines, customers)? Is it a method to provide and display visibility and the behavior of costs? A way to think about cost accounting can be with an analogy from physics and

Enron, WorldCom, Satyam — six famous failures that passed every spreadsheet test. The numbers always added up; the chain of trust around them didn't. In Profitability Analytics, where no regulator audits your allocation Rule Sets, that same gap is wide open. Why validation isn't governance — and what a CFO should do this week.

As we are unable to provide a replay (technical difficulties) for this webinar, I have instead provided a summary. Executive Summary: AI, Analytics & Automation for Business Growth Based on the webinar presented by Chandan Jha This webinar explored how artificial intelligence (AI), analytics, automation, and digital transformation are reshaping operational performance, profitability, and strategic decision-making across modern organizations. The session focused particularly o

If we measure AI adoption like a participation trophy, don’t be surprised when the market thinks it’s winning. Every business leader is now talking about AI adoption — and most professional services firms think that adoption alone is progress. But let’s get real: flipping the switch on a tool doesn’t magically generate value . Without disciplined ROI frameworks and unit-economics tracking, we’re on a fast track to repeat the same tape-measures-for-success mistake we saw in t

The Hundred-Day Blind Spot It was late October, and Mark Ryan, General Manager of GlobalTech, sat in his office staring at a consolidated financial report that was exactly 104 days out of date. Outside his window, the market was shifting at an unprecedented pace. Inside his rapidly expanding technology enterprise, time seemed to stand still. GlobalTech was a victim of its own success. For three years, the company had ridden a wave of strong market demand, expanding its produc

Post by Lukas Rieder The executives of a company must ensure that it achieves a market-driven return* on the invested assets. Only then will investors take the risk to invest in that company. For me these executives and their direct employees are PACE's key customers. They need a management control system allowing them to plan and control the variables they can influence directly and independently in their area of responsibility. This has little to do with financial accountin

Boards often assume value arrives when the model goes live. Reality: value arrives when behavior changes —when decision processes change, old work stops, and economics show up in unit measures. AI creates outputs immediately. But outcomes lag. And the lag is not a technical defect. It’s an organizational reality. The staged value curve most business cases pretend doesn’t exist What I see repeatedly: 4–12 weeks: operational signals (usage, cycle time in a narrow workflow, few

When AI investments underperform, the post-mortem usually devolves into debate: “The business didn’t adopt it.” “The data wasn’t ready.” “IT didn’t integrate it.” “The vendor overpromised.” All of that may be true. But the deeper problem is governance: the investment was approved on assumptions that were never made explicit—so nobody can own them, monitor them, or trigger decisions when they break. When assumptions remain implicit, accountability becomes politics. Everyone ca

In a North American boardroom, organizational leaders convened for their fifth finance transformation initiative in less than a decade, approaching the effort with a mix of optimism and skepticism. Over the course of these unsuccessful attempts, the organization invested more than $25 million and over 30,000 employee hours without achieving the intended outcomes. The escalating costs, diminishing momentum, and leadership fatigue transformed each new launch into an indicator o

Most AI business cases still feel “clean” because they’re built from what’s easy to count: licenses, a project team, maybe some IT time. That’s not AI economics. AI economics don’t live in purchase orders. They live in activities —the recurring work required to keep the tool producing usable, decision-grade outputs at scale. The costs you don’t see (until you can’t ignore them) If you want total cost of ownership (TCO), stop asking “what did we buy?” and start asking “what wo

It's Saturday and over morning coffee ☕ I started looking at facts about accounting - historical and current. Here is what I found: 1️⃣ Management accounting predates financial accounting. Cost tracking for internal decisions existed centuries before standardized financial statements were a thing. Owners cared about control long before compliance. 2️⃣ Standard costing was basically the original “performance dashboard.” Variances were an early form of KPI monitoring—long befor

I have been thinking a lot about what might happen in 2026 and although there is a lot of uncertainty – especially right now -, uncertainty seems to be becoming the norm rather than the exception. For that reason, I think the competitive advantage will not belong to the organizations with the most data, the most AI, or even the fastest analytics, it will belong to those that can adapt quickly to evolving situations and translate insight into economic control . For CEOs, CFOs,

Risk oversight has become a central responsibility for boards and senior leadership teams. Yet many of the most consequential risks organizations face today do not appear suddenly. They emerge gradually, often hidden within seemingly acceptable financial results. By the time traditional metrics signal a problem, leaders are already reacting rather than governing. I’ve observed that this happens because risk is frequently assessed through lagging indicators—variance analyses,

Few things concern boards and CEOs more than the gap between strategy and execution. Most organizations have well-articulated strategies. They invest significant time and energy defining priorities, setting targets, and approving initiatives. Yet months later, leadership teams often struggle to explain why results diverged from expectations—or where accountability truly lies. In my experience, this gap rarely stems from poor intent or inadequate effort. It stems from a lack o

In my experience, the challenge is not a lack of financial data. It is a lack of integration and causality . Most organizations measure revenue, costs, and investments in separate systems, using separate models, for separate purposes. Each view may be technically sound, yet together they fail to explain how decisions actually create—or erode—value. As a result, boards and CEOs are often asked to evaluate strategic initiatives without a clear line of sight into their profitabi

Over the years, I’ve worked with boards, CEOs, CFOs, and senior leadership teams who are deeply committed to improving performance. What consistently surprises them is not a lack of effort or intelligence—it’s how little visibility they have into why profitability behaves the way it does. Financial statements are essential. But they were never designed to support strategic decision-making. They tell us what happened.They rarely tell us why it happened.And they almost never