Here is Warren Buffet's 7 principles to investing:
1. Managers must have integrity and talent
2. Invest by facts, not emotions
3. Buy wonderful business at fair price
4. Only buy stocks you understand
5. When you see a great opportunity, take it
6. Don't sell unless the business fundamental changes
7. Buy at a price below intrinsic value
If any work disciplines can offer us a window to the future, Financial Planning and Analytics (FP&A) is certainly one of them. In an environment where your speed to move can make the ultimate difference to your company, it’s no accident that financial forecasting is now at the cutting edge of change in today’s business world. And indeed, future business success may lie with those who embrace these changes sooner rather than later.
Faced with a post-Millennium atmosphere of uncertainty and rapid change, accurate forecasting – and the ability to reforecast at pace – has gained huge currency for business leaders. Add to this the influence of automation tools on traditional accountancy roles, plus the growing need for top-line expertise in reading and disseminating our vast quantities of data, and you have a sector at the centre of the action when it comes to change. Michael Page recently sat down with one of FP&A’s thought leaders to plot five factors driving change in today.
1. Speed and Simplification
Larysa Melnychuk, CEO and founder of the International FP&A Board, spends much of her time these days in discussion with the world’s leading CFOs about the changing world of financial analytics, financial planning and analysis.
She notes that in an environment of unprecedented “black swans” and “perfect storms” in our global financial market, business leaders are now more aware than ever of the need to move fast: “Situations that we never expected would happen, have happened in real life. Obviously in the business environment, this is one of the biggest reasons why financial analytics has changed,” she notes.
Combine this pressure-cooker environment with the arrival of newer and cheaper Cloud-based systems that are easily managed within a finance department, and you have an environment ripe for change. “In this dynamic business environment, it’s not possible to use the old, very detailed and static methods we used,” notes Melnychuk, who is based in the United Kingdom. As a result, the landscape for financial analytics is now more forward-looking and speed conscious than ever.
2. Find Your Key Drivers
In an increasingly complex environment, the ultimate goal is to understand in the simplest way, how a business makes its money. “We’re talking about simplification beyond the incredible level of detail that we had before,” notes Melnychuk. “It’s all based on key business drivers that are very important to identify – it’s about the 20% of drivers that explain 80% of the results.”
She notes that while many managers claim to know these key drivers, the reality of our big data world is that some drivers become less sensitive over time, while others prove less reliable. The ideal key drivers process should be part of a company’s business intelligence project, she notes. “It should be automated: and the drivers should be checked often, through analytical automation.” Likewise, it is also important to pay attention to both internal and external drivers, she notes.
Yet are many companies in the world currently doing this? “I would say not many,” she notes. “Definitely leading companies have started – and this is on the agenda of many companies.”
3. Tough Roles to Fill
Increasingly, she says modern FP&A teams require three distinct roles (as per Mark Gandy’s model). The first is the Architect who builds the driver-based model. Next comes the Analyst, who can track its progress. And ideally, a third role, that of a business-partner, or Communicator. “It’s difficult to find these three people in one role,” Melnychuk notes from her own experience as an FP&A director. “Analysts and Architects can be introverts, and not so comfortable going to the business to communicate it. I’ve seen this a lot.”
As such, it tends to be a tough job to fulfil: “Around 70% of UK CFOs, and 80% of US CFOs, say that FP&A roles are the most difficult to fill.” While in traditional accountancy, being qualified and examining past financial history was once sufficient, this is no longer the case. “In FP&A it’s different. We’re seeing the emergence of big data, from which you have to analyse these key drivers.”
4. Rapid Reforecasting
In an environment of sudden and intense market change, being able to identify and simplify your business drivers can provide an invaluable chance to move fast against competitors. “It’s dependent on the visibility of their data, and the ability to drill down and make decisions very quickly,” Melnychuk notes.
She takes the example of a sudden market interruption, a so-called black swan event. “With traditional planning models and traditional hires, you needed four-to-seven months to reforecast. But with this new generation of systems, models and people, you can probably do this in a couple of hours – almost in real-time.” One New York based banking group she spoke with, had reforecasting down to a fine art. “At the moment, it’s less than 36 minutes, while previously it used to be more than three weeks. This is an indication of how the world’s changed,” she notes.
“And why? It’s because traditional line-by-line forecasts were replaced by driver-based planning model that is implemented through system. Just 36 minutes and it’s done – and the quality of this forecast is quite good as well. So this is a good example of how much this can achieve.”
5. Future role replacements
Melnychuk anticipates a realignment ahead in terms of job roles within finance departments, as some traditional roles become replaced by new ones. “Fewer traditional accountants will be needed, and more combinational skills, especially with this data management, analytical and business-partnering will be needed,” she predicts. “I can see a time when data scientists work together with FP&A. And it is already happening in some leading analytical organisations”
Leading companies already enlist data scientists to identify, for instance, the one driver responsible for 60% of their forecasting. Melnychuk notes that effective driver-based planning can save teams a lot of time and effort: “You don’t need a lot of data, or to spend a lot of time. But to identify those key drivers really can help you to very quickly and very effectively build your plans and different scenarios for the future.”
“There will be this new work for analytical people, because they will start from different levels of analytics, and they will go forward. So it’s very motivational for good analytical talent to be at such organisations.”
Source: Luke Clark
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