Integrating Financial Analytics with Operational Transfer Pricing to Optimize After-Tax Profitability – Part 1

From Rob Jenkins, SAP Global Center of Excellence

Benjamin Franklin once noted “In this world nothing can be said to be certain, except death and taxes.” Finance professionals must deal with uncertainty as they model the future and partner with the business to optimize decision making. And while taxes are a certainty, tax jurisdiction and therefore tax rates are a function of how and where a business process is executed and assumptions made by the business. And those assumptions should be well documented for regulatory agencies.

Every for-profit entity’s objective is to deploy capital to maximize the after-tax return on investment. This requires a tight collaboration between financial planning and analysis (FP&A) and corporate tax functions to provide insight into the past and potential economic profit of products and customers and the available possibilities of organizing operations to maximize after-tax profit.

Many companies are in the news for performing “tax inversions” as part of a strategic acquisition of a non-US-based entity due to U.S. rates now exceeding the simple average of other OECD nations by 14.1 points and the GDP-weighted average by 10 points. [1]

Modeling After-Tax Financial Impact of Business Operations
Given the disparity in global tax rates, process and asset location along with transfer prices can have significant impact on after-tax income. Various operating scenarios can result in “profit shifting” among tax regimes and the business analyst can calculate the impact on statutory results by modeling the following:

  • Whether a business activity is active or passive
  • Where activities occur including R&D and “management”
  • The location of intellectual property
  • Placement of debt and borrowing costs (thin capitalization rules)
  • Transfer pricing (inter-company pricing arrangements between related business entities)

Choosing the Right Tool for the Task
A variety of tools are available to enable business users to estimate financial outcomes based on input variables and assumptions about their systemic relationships.

Spreadsheet technology is ubiquitous in finance for ad hoc modeling with some companies building complex, interdependent workbooks with macros for automation and detailed documentation for knowledge management, while others rely on a single subject matter expert to maintain the “black box”. These webs of interconnected cells and sheets are notorious for their error rates and hardwiring with one study finding “errors of at least 5% were found in 91% of all spreadsheets with more than 150 rows.” [2]

My previous blog post, Big Data for Finance, referenced how Big Data and analytics can be utilized to model the future based on historical data relationships and advanced analytic algorithms – though few finance organizations have yet to embrace the suite of predictive analytic tools now targeted at the business user.

Managing the Scope of Planning, Budgeting and Forecasting Systems
However, most finance organizations are using enterprise software applications for planning, budgeting, and forecasting with a large number of firms incorporating driver-based techniques for quantifying revenue forecasts and gross margin (for example, estimated product volume x selling price and standard cost for cost of goods sold).

For planning indirect operating expense including the cost to acquire, serve, and retain customers, the vast majority of companies budget expenses by function, responsibility center, and account, and rely on streamlined allocations to create a pre-tax operating margin view with most management attention focused on “controllable margin.”

These enterprise planning systems are extremely valuable for gathering inputs from decentralized sources, managing workflow, recording audit trails, aggregating actual results, calculating budget variances and reporting multi-dimensional financial statements for management.

Since FP&A teams are traditionally focused on financial reporting aligned with GAAP or IFRS requirements, these planning systems are rarely configured to calculate the detailed dynamics of how hundreds or thousands of shared indirect labor or overhead cost pools are attributed (sometimes in multiple steps) to products or customers based on usage-based drivers or activity-based methods.

Nor do these systems typically account for the tax impact of supply chain logistics, asset location, and transfer prices. Complex driver-based attributions and operational transfer pricing have been the province of cost accounting and tax accounting, respectively, and rely on specific techniques, operational data sets and levels of detail not ordinarily integrated into corporate planning systems.

The result is that most FP&A and tax teams use separate systems to plan and model pre-tax economics at a high-level vs. a granular view of profitability by customer and product vs. the tax impact of how business operations are organized.

So, what’s the solution? In my next blog, I will discuss operational transfer pricing and the rise (again) of profitability and cost management software. Stay tuned!

[1] Tax Foundation, OECD Corporate Income Tax Rates, 1981-2011, http://taxfoundation.org/article/oecd-corporate-income-tax-rates-1981-2011.

[2] http://www.isaca.org/Journal/Past-Issues/2007/Volume-1/Documents/jopdf0606-controlling-spread.pdf

 

Integrated Business Planning: Will Disruptive Tech Help or Hinder?

Coffee-break with GameChangers

“Understand the future that has already happened.” This quote from venerable business consultant Peter Drucker was invoked by Steve Player, North American Program Director for Beyond Budgeting, in one of a series of SAP Game-Changers radiocasts. Three guests visited the program and were asked to offer their thoughts on budgeting and forecasting – and here’s what they had to say.

When it comes to integrated business planning, CFOs might want to decipher and heed Drucker’s advice. According to roundtable experts, it might be C-level executives who are keeping companies behind the eight ball.

Budgeting and forecasting success are dependent upon a comprehensive understanding of the business and a keen ability to predict future trends.

But how do we achieve this? Are disruptive technologies such as enterprise mobility, cloud, and in-memory computing the answer to implementing integrated business planning enterprise-wide?

Jeff Hattendorf, cofounder of IT consultancy firm Macrospect, believes they are. He cautions that strategy and financial planning need to be separate activities. It’s the responsibility of the CIO and CFO to herald the arrival of tools that integrate planning, operations, and finance at an operational level and at a level of detail that line managers can put to good use.

Let Go of the Budget
“In many cases the CFOs tend to be the ones that are holding everybody back,” agrees Player. They become attached to a certain budget and want to quickly close the books, without considering the overall health of the business. But Player says the budget is out of date before it’s even finalized. Placing so much focus on a defunct budget can hinder forecasting and predictive analytics.

Rather than keeping score and getting hung up on meeting a certain number, CFOs should focus on something more strategic and long-term, according to Floyd Conrad, Senior Director of EPM and Finance with the SAP Center of Excellence. He claims it is much easier to create a balanced budget and an actionable strategic plan for a company if you rely on new predictive and in-memory technologies.

Chart a Quest for Vision, Not for Speed
As any executive will tell you, reports don’t become more valuable simply because they run faster. Hattendorf explains that adopting technologies to speed processing should be done within the larger framework of achieving a clearer, more detailed view of business processes.

Player thinks the whole reporting concept should be completely reimagined, since reporting speed dictates how quickly insights are uncovered. The objective should not be finding a quick fix, but preventing problems from occurring in the first place. For example, find out when people need information instead of what kind of information.

For integrated business planning to succeed, CFOs and CIOs need to collaborate more and become early adopters of technology that prepares them for ups and downs in ever-changing markets.

Player is so optimistic, he believes that the notion of integrated planning won’t be a point of discussion in the next five years. It will happen so naturally that no one will consider it newsworthy.

Is that a wager you’d take? Dive deeper into this debate and listen to the whole radiocast.

Forecast with improved accuracy – leveraging BIG Data and Predictive Analytics…What!?

From Jonathan Essig, EPM Solution Director, NTT DATA Enterprise Services, Inc.

The question that has been nagging at me lately is this: why aren’t more finance organizations leveraging BIG data and predictive analytics? Is the answer, they don’t know how? Is it, they can’t pin point the value it will bring? Or even possibly, they don’t really know what BIG data is?

From what I have seen it is a combination of all three but breaking down these barriers can help the office of the CFO leverage these new technologies. Doing so will greatly improve planning accuracy, profitability analysis, and ultimately drive better decision making.

First, what is BIG Data?

For Finance organizations, BIG data can seem intimidating or a bit of a mystery. In fact, it seems as though everyone is talking about it but no one can quite define it.

Simply put, BIG Data means “data sets that are too large for traditional processing…and require new processing technologies”. Many companies have already seen the power of in-memory technologies, such as HANA, demonstrated by retrieving back millions of rows of data in seconds. This is truly impressive, but Finance executives secretly, or not so secretly snicker about what real value that can add for them. Really, it is the insight we can now extract from the increasingly large data sets that holds the opportunity. In other words, what is important is what we can do with the big data – not the big data itself. Applying predictive analytics to BIG Data is one great way to mine your data for value. As finance organizations change their mindset to viewing data as an asset, they will be better positioned to take advantage.

How can Finance organizations use Predictive Analytics?

Predictive analytics enable organizations to leverage big data to develop more accurate and timely forecasts. Specifically, predictive analytics can better analysts’ ability to foresee product demand by customer or by region. The BIG Data used for this analysis can be hidden in many places – CRM, POS system, social media, historical trends, and other macroeconomic data sources.  Predictions from these models can be fed real time into your planning tool and applied as a starting point for a rolling forecast each month.

This means you can see the profitability impact of drivers REAL time and use it to better business decision making! For example, you can model profitability with predicted changes in volume, pricing, raw material costs, inventory, receivable etc and allow management to adjust their strategy before the competition.

Why now and what is the value of Predictive Analytics with BIG Data?

Predictive Analytics has been in the news quite a bit in the last couple years as relates to consumer product companies and targeted marketing.

Companies have hired teams of consultants and analysts to come in and complete regression analysis on their POS data to identify for example, customers whose purchasing habits make them most likely to buy specific products in the future. Not surprising then that sales organizations tend to be earlier adopters than Finance organizations, but this has also been in large part because of the LARGE, measurable benefits they have obtained.

However, in the finance world, the benefits are much harder to measure and it is tough to justify a big initial investment. What we need to do is make the benefits measurable and lower the initial investment.

One of my favorite quotes from Galileo, “Count what is countable, measure what is measurable, and what is not measurable, make measurable.” Well said…

Thankfully, new technologies are bridging part of the gap.

SAP’s newest Predictive Analytics tools have taken the grunt work and hours of statistical analysis out of statisticians’ hands and made this very accessible to the typical business analyst. Predictive tools do this by providing prepackaged algorithms and an easy to use interface requiring no advanced statistical knowledge or programming. Literally with a few days of training, finance teams can analyze historical trends, CRM data, or other macroeconomic data to provide a much more accurate starting point for their forecast. Essentially, allowing them to “measure” and benefit from what was previously very challenging to do so. How do I know how easy these tools are? I have worked hand in hand with SAP developing a predictive planning use case for them and was able to hit the ground running in less than a day – and I am no more technically savvy than your average finance or business analyst.

All of the above are now enabling finance organizations to talk about Predictive analytics and BIG data intelligently and understand the applications.

Another great quote by one of my favorite authors, Oscar Wilde “Experience is the name everyone gives to his mistakes” . Those willing to gain the experience and make some mistakes along the way will be the ones to deliver their organization much greater planning accuracy, unparalleled profitability analysis, and will ultimately drive better decision making.

For more information listen to my latest appearance as guest expert panelist on Voice America’s talk radio, or start getting acclimated by viewing the beta webcast below (use case has been updated and honed since original presentation). Here are some links to follow:

Voice America SAP Radio Financial Excellence talk show

Webcast recording Maximum Agility with Big Data for Finance

Going to SAP Financials in Nice? This blog could get you in the mood.

and finally…another great blog entry on Big Data

 

BIO: Jon Essig is an EPM solutions expert. He has architected many solutions, working with c-level execs, corporate finance, regional business units, and IT to create and implement a company-wide vision. He has delivered analytics, consolidations, and planning across a variety of industries. Jon also has close to ten years of experience as leader in various financial roles including: consolidations, financial analysis, forecasting, audit, SOX, financial closes, and tax. He has a great passion for innovative technologies and is an early adopter and architect of big data and predicate analytics applied to Finance. Jon holds a B.S. in Finance and is a Certified Public Accountant.

Contact Jon: jonathan.essig@nttdata.com | linkedin | @JonathanEssig

The Goal of FP&A: Future Profits Assured

From Steve Player, North America Program Director for the Beyond Budgeting Round Table (BBRT)

Last week’s blog discussed the continued expansion of the roles that CFOs are asked to play. This week we go deeper into the new role of “promoter of predictive analytics.” With the power of new technologies, many CFOs are moving to driver based forecasts that can serve as early indicators of future performance. While FP&A departments typically stand for Financial Planning and Analysis, many CFOs would prefer it to stand for “Future Profits Assured.” Let’s explore how predictive analytics are moving organizations closer to that goal.

As their name implies, predictive analytics provide insight into what is coming. In my mind it also conjures up memories of the spring rains of 2011 that led to widespread flooding along the Mississippi River. While property damage was great, the loss of life was mitigated by early warnings of when and where the rivers would crest. These were based on where rain was falling across each river’s watershed area compared to the time needed for it to flow downstream. Simply put too much water coming too fast creates a flood. Getting real time information still leaves you at risk. You need predictions.

Faster than real time. Likewise, great CFOs have learned to look far upstream to see what is coming at them. They are moving beyond data mining by tapping into deeper insights provided by predictive analytics. By identifying which variables are most predictive of profitability— and it’s never just one— the CFO defines fewer, more accurate scenarios for future outcomes. A sound approach measures the ability of an internal predictive computing effort to reduce variability and increase certainty. Doing so transforms finance from being a spectator staring off the back of the company’s boat into an early warning system helping the captain more successfully avoid risks and achieve objectives. While you often hear that finance should become a “trusted business advisor to operations,” delivering predictive insights is the goal of FP&A departments that are considered a key part of the complete business team.

Clouds, Dusseldorf, North Rhine-Westphalia, Germany

Weather forecasters are role models. Nate Silver writes in The Signal and the Noise that [i] weather forecasters maintain a “healthy balance of computer modeling and human judgment” that is lacking in other disciplines. A good weather forecaster calls other forecasters to compare notes. The savvy CFO has a roadmap for how inputs from social data— whether it’s as simple as where people go, or as complex as what kinds of information people search for— impact firm performance. CFOs are learning how mobile data can provide geo-location data to better understand and reach customers. Tapping into these vast social media vaults enables real time sentiment analysis that can predict future customer actions.

The weather forecaster has good hair. A unique example of these techniques in action comes from the Weather Channel. In 2013, the Weather Channel created a “frizziness index” for Proctor & Gamble’s Pantene shampoo brand. Women checking the Weather Channel forecast in the morning saw a custom set of Pantene ads. Retailers saw a spike in Pantene sales on days when the forecast (hot and humid) called for frizzy hair. (On a low humidity day a volumizing product is recommended.) Predictive computing helps the Weather Channel target three million global micro-climate locations, generating revenue by innovatively using data it was already capturing.

Whenever you see a weather forecast, ask if your organization is taking full advantage of the power of predictive analytics. There are typically a lot more benefits to be gained.

Your head is likely swimming with all the possibilities. Next week, I will show you how you focus in on a critical few items which should be key to your success as our discussion turns to aligning execution to strategy.

 

[i]http://fivethirtyeight.blogs.nytimes.com/2012/09/09/why-weather-forecasters-are-role-models/

 

Steve Player

The Expanding Role of the CFO

From Steve Player, North America Program Director for the Beyond Budgeting Round Table (BBRT)

In my continuing interviews of chief financial officers, I am amazed at the breadth of their job responsibilities. In his excellent 2006 book Reinventing the CFO, my late colleague Jeremy Hope described seven keys roles that CFOs were playing. If he were writing an update today, he would likely find twice as many roles.

CFOs face a key challenge in selecting and focusing on a few strategic and tactical roles that provide true advantage for their firm. Examples of these roles include analysts and advisor such as providing customer profitability analysis, regulator of risk in effectively managing their firm’s risk, and warrior against waste in reducing non-value added costs. As the basics of accounting and cash flow are mastered, your team is freed to apply finance skills to areas of greater impact.

One of the most discussed technologies transforming the finance function is in-memory computing. With expected market growth of 43 percent per year, it’s fueling both business mobile applications and predictive computing.[i] The following three examples illustrate how in memory computing is being used to harness big data:

Businessman analyzing pie chart on digital tablet

CFOs are becoming deluxe dashboard designers – Many traditional finance organizations assist the operating units by providing key performance indicators (KPIs). While this role started out as all about the numbers, organizations have learned they need a balanced set of measures that are both physical and financial. This greatly expands potential KPIs but requires sharp design skills to avoid being overwhelmed by data volumes.

In-memory computing is helping Lenovo, the world’s second largest PC vendor meet this challenge using SAP HANA.[ii] This resulted in significantly faster processing as time to process 1.8 million contract records dropped to a few seconds. KPIs no longer exist only in the data warehouse— they can be changed on the fly and made available in multiple formats and geographies immediately. Lenovo also deployed self-serve reporting to the business – reducing the time to produce reports based on tens of thousands of rows to about 10 minutes, compared to 3 hours before.

CFOs are becoming collaborative customer advocates – Using HANA, Lenovo has shifted its KPIs to take a more customer focused approach. The old approach focused on internal measures. The new approach provides greater order visibility. It measures what customers are interested in such as requested receipt date rather than promised date. Using KPIs that better capture the voice of the customer provides a more effective collaborative improvement approach. Analysis can is also enhanced by overlaying customer profitability information (which will be discussed in a future blog).

CFOs are becoming innovative information integrators – In-memory computing is helping CFOs find more innovative ways to integrate information. For example:

  • Risk management is being improved by quickly analyzing large sets of social data. One insurance company uses a blend of structured and unstructured data to assess the validity of a claim. Are the witnesses to the claim also claimants in other cases? How well do the parties know each other? Are they connected on social networks? An integrated view of these connections can be the key to truly understanding fraud risk even as fraud tactics change frequently.
  • Supply chain coordination runs smoother when information is shared across the entire chain rather than just within a single organization. Sensors are providing far more data inputs to the supply chain. In-memory processing is required to handle these rapidly expanding data points.
  • Sales forecasting information is greatly enhanced by overlaying both multiple viewpoints of projected outcomes. These integrated views provide both consensus and outliers perspectives. Other external measures are also being compared to identify correlations to improve future projections.
  • Expense management can be expanded to an enterprise-wide basis regardless of enterprise size. With in-memory computing even as organization as large as Hewlett-Packard can improve the value provided by their financial analysts and enhanced decisions making (see here for a deeper look at their recent implementation of SAP HANA).
  • Integration of business planning is also enhanced by in-memory computing as it enables multiple types of data to be integrated (see also my earlier blog on the topic of business planning). Physical data can be combined with financial data to build predictive logic diagrams. Statistics can be applied to better understand cause-and-effect relationships. The ability to quickly and easily combine this information enables planning managers to more deeply understand where the organization is headed and what activities can shape the ultimate results.

This blog just begins to scratch the surface of what is coming. More uses are being added daily. CFOs with a solid understanding of in-memory computing will ensure their finance function can act with greater awareness, insight and agility.

Next week, I shall look at how these tools are enabling finance to become much more predictive and how that can improve your business.

 

[i] For more detail see the “Global In-Memory Computing Market 2014-2018” published by Research and Markets in Nov. 2013 at http://www.researchandmarkets.com/research/6cs4nz/global_inmemory

[ii] For more on Lenovo’s implementation of HANA see http://events.sap.com/sapphirenow/en/session/2441

and: http://www.sap.com/pc/tech/in-memory-computing-hana/customer-reviews.html

 

 

 

 

 

 

 

 

 

SAPinsder Financials Comes to Europe, 21-23 May in Nice, France

SAPinsiderNice

Following a successful show in Orlando in March, it’s nearly time for the SAPinsider conference to open its doors to a European audience with SAPinsider Financials taking place in Nice, France, 21-23 May.

Looking at the conference agenda, I can see that the Nice event will be no-less packed with Finance and EPM content than its Orlando counterpart, which means this is the event to attend this year for anyone interested in these solution areas.

If you’re planning to attend the event, what are the key topics and themes you should look out for? The response to that question could vary considering the breadth and depth of sessions at the show. But if you’re interested in EPM then I’d suggest that you focus on sessions involving hot topics like mobile EPM and in-memory computing, and customer case study sessions, which contain exciting content as they relate to the customer’s experience with EPM solutions.

Here are a few sessions I recommend:

My advice, as it was for Orlando, is to plan your show long before you catch the flight, this way you’ll get the most out of your time. The online agenda is a great tool to review and select sessions for your topics of interest. In addition to the conference sessions already mentioned, don’t forget the excellent pre-conference workshops for attendees wishing to dive deeper into their subject areas.

Have a great show. And don’t forget to follow the @CFOKnowledge twitter handle over the next few weeks for links to more EPM sessions at SAPinsider Financials 2014 in Nice.

Robust Planning for Future Generations

From Steve Player, North America Program Director for the Beyond Budgeting Round Table (BBRT)

In my last blog I talked about some of the steps CFOs and finance teams are taking to make sure that both the finance function and their entire organization is “future ready”. When looking at the finance function of the future, the first key thing to note is that smart CFOs have stopped focusing on shrinking the finance staff. Efforts to reinvent finance started over 20 years ago. The goal was to transform finance by eliminating low value tasks and replacing them with strategic decision support. If you analyzed finance team activities in the 1990s, you typically found that about two-thirds of work time was consumed by low value transaction processing with the remainder split with one-sixth going to financial control and the remaining one-sixth left for decision support.[i]

Since then, continuous waves of finance improvement projects have delivered results. When Hackett Group started benchmarking finance functions in 1992, the overall cost of the finance function as a percentage of sales were originally about 2% of revenue. Those costs have now dropped down to the current range of ½% to 1% of revenue.[ii] While that reduction is good news, the overall breakout of activities remains with two-thirds still going to transaction processing. Smart CFOs have realized the need to truly transform finance by changing the work their teams perform.

Budget Meeting

One of the areas experiencing the most change is planning, budgeting and forecasting which is transforming into next generation planning philosophies, processes and supporting systems. Enlightened finance teams are realizing the futility of spending four months negotiating annual budgets in a world that is constantly changing. A good analogy would be trying to steer a ship by looking backward at the ships wake. This is particularly true when you consider all the assumptions the budget is based on. Companies are moving to a forward-looking planning process that integrates strategic planning, forecasting, and rapid comparison of actual reporting information. This approach has several key advantages. These include:

  1. Constantly available – An integrated business planning system is always ready for continuous planning updates to respond to a changing environment.
  2. Collaboration – An integrated business planning system is designed to share information across multiple functional silos. It is designed for interaction between different parts of the business.
  3. Consensus building – An integrated business planning system allows managers to see how actions in one area impact results in another. Seeing the whole enables managers to develop combined plans that optimize potential results.
  4. Complete picture – An Integrated business planning system provides a complete system that offers views of future horizons, and also combines to show consolidated impacts when results are closed. This includes capital plans and understanding the impacts on cash flow. Organizations are more successful when they can see all the impacts.
  5. Cost Effective – Leveraging an integrated system to eliminate the need for multiple data inputs when items inevitably change. Linking plans also helps teams communicate changes and coordinate appropriate responses. It promotes one version of the truth to be used by all.

Finance transformation truly occurs when finance teams stop doing dumb stuff (which stuff even if done correctly provides limited benefits) and utilize the time freed up to provide an integrated business plan that is robust enough to assist in multiple future scenarios. This is critical for companies like Statoil that operate in quickly changing environments. Thinking through a wide range of scenarios makes them future ready.

Next week, I will look at the new technology drivers that are enabling these more powerful systems. I will examine how in-memory processing enables these planning systems to take flight.

 

[i] For a detailed discussion, see the Statement on Management Accounting “Redesigning the Finance Function” published by the Institute of Management Accounting, 1997. This report uses finance metric benchmarks published by The Hackett Group. 

[ii] See David Axson Best Practices in Planning and Management Reporting (Hoboken, NJ: John Wiley & Sons, 2003) p.7-8. 

[iii] See “The True Measure of Finance Function Excellence: Deliver Value Efficiently” white paper published by the APQC in 2012 and Improving Decision-Making in Organizations: The Opportunity to Reinvent Finance Business Partners” report from Chartered Institute of Management Accountants (CIMA) in 2010.

Steve Player