1. Man is a tool-using animal, and treasury technology is a tool that allows more work to be accomplished 2. Properly used, Treasury technology allows a company to operate in 3 dimensions, simultaneously managing profitability, liquidity and risk 3. Improperly used technology allows a company the opportunity to make its mistakes faster 4. Today’s technology (spreadsheets, emails, multiply…
“HR executives are well-equipped to competently manage the basics – recruiting, hiring, onboarding, payroll, benefits, training, etc. – and operating unit general managers are generally satisfied with the results. The typical missing link for HR executives, however, is often their ability to assist general managers with the more strategic issues, like:
Are we better off keeping our geographic sales structure after the acquisition, or do we now have sufficient critical mass and concentrations of expertise to take an industry-centric approach?
Can we predict how the increased average age of our skilled workers, their upcoming retirement and the massive replacements by inexperienced workers will affect the business?
The increased production and sales capacity is going to make R&D the bottleneck; what are the critical technical skills we’re going to need and what is the optimal mix of hires, layoffs and retraining to counteract that bottleneck?
In order to meet the increased seasonal demand from new customers, should we build inventory early, run additional shifts or outsource some of our production needs?
It came as a bit of a shock that some customers just weren’t going to pay you. For no good reason. I would ask if perhaps the delivery had been short, or was late, or something went wrong with the implementation, or they were trying to use it as leverage on another deal, or maybe they were having cash flow problems themselves. If so, we could work something out. No, it wasn’t any of those things, this was simply how they treated all their vendors, they’d pay us when they felt like it, or maybe they wouldn’t pay us at all.
What type of data do our brains need to evaluate one of the most important aspects of business planning, ie The Forecast?
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As leaders and managers of human beings with million year-old brain structures, as part of our managerial toolkit we need to keep ourselves knowledgeable about psychology and the cognitive science of how people make decisions. You have undoubtedly read about how innately bad we are at making certain types of decisions, especially those involving risk, probabilities and shifting time horizons.
Part of the reason for this difficulty is the structure and function of our three-layered brain. The complexity and size of the neocortex, especially the pre-frontal cortex, is a very recent evolutionary development. Prior to this development, our mammalian ancestors still made decisions, but they did so relying heavily on the more intuitive, emotional limbic layer. It would be fairly accurate to say that our emotions are simply a different way to make a decision. It’s quick, can still be trained by experience and learning, and can be wired directly into rapid motor responses that most likely saved our ancestors lives countless times, who faced more binary decisions than probabilistic ones. Gut-feel is really “brain-feel”.
When you begin your career your most important skills are your hard, technical skills; the finance and accounting, the statistics and economics, the physics and chemistry, the engineering and calculus. But as I tell my business school mentees, as your career progresses, the emphasis changes such that much sooner than you might initially think, the most important courses you took in college turn out to be psychology, philosophy, literature, sociology and anthropology.
We all bring important skills to the myriad of different conversations we participate in every day, and while confrontation and intervention might not be your cup of tea, applying the right type of analytics to the problem, consistent with its level in the Conversation Pyramid, can immediately make you and your team valuable in either catalyzing your own organizational transformation, or simply improving your organization’s value creation or mission effectiveness.
Best-practice financial planning and analysis (FP&A) teams are looking for ways to venture beyond the traditional job scope. Previously, the typical FP&A team spent the bulk of its time reporting on how well the organization had performed during a given period versus pre-set targets. The team may have also helped to develop contingency plans in the wake of performance short-falls. Today, more FP&A teams want to do more than keep score. They want to engage in predictive analysis, which anticipates fluctuations in customer demand, revenue flows, and costs over the course of upcoming periods. They also want to support decision makers with analysis-driven contingency plans that can be implemented if and when conditions in the marketplace shift.
Antiquated processes and tools combined with misconceptions regarding forecasting accuracy have hindered the quality of forecasting processes around the world, producing often questionable forecasts. Yet, organizations have good reason to strive for accurate forecasts.
Whether you know it or not, you are already doing driver-based budgeting and forecasting with your spreadsheets today, but in a very restricted fashion, with only one primary driver, typcially ‘headcount’ for most line items, and defaulting to a weighting of 100%. Not terribly sophisticated, not at all transformative, but ever since VisiCalc it’s been all we’ve had to work with.
Those days are now over.
It’s no secret that business and finance professionals are spending too much time on mundane tasks, and not enough on delivering insight and other value-added activities.
A recent survey shows that while the process of generating budgets, plans and forecasts has stayed relatively static, business professionals are spending increasing amounts of time wrangling data and manipulating inadequate toolsets to deliver the budgets, forecasts and strategic plans that drive company decision making.
Where does all the time go?
Data scientists who do mashups from disparate data sources are able to gain deeper insights into problems and develop more comprehensive approaches toward attacking them by having a richer data set to work from. In turn, data mashups can help companies become more agile and speed time to market.
Consider the use of customer data.