Monthly Archives: December 2014

Strategic versus Operational Planning: Tale of a Tug-of-War

December 23, 2014

Have you ever been in a situation where your CFO asks you to tweak a few assumptions on your operational forecasts and wonders why it takes many hours or even a few days to review an updated operational forecast? Or asks you to convert the operational forecast just by rolling up numbers at a parent level to arrive at a strategic forecast to review with the Board of Directors? Most organizations experience such challenges and experience a tug-of-war between operational and strategic planning.

Operational planning primarily involves the Financial Planning and Analysis (FP&A) function, whereas strategic planning involves the breadth of Corporate Finance (and related) functions such as FP&A, Treasury, Controllers, Corporate Strategy, Tax, and Legal. To understand the nuances of operating versus strategic planning, let’s contrast the components of operating and strategic forecasts.

Operational planning typically includes department-level operating components such as operating revenues, cost of goods sold (COGS), compensation expenses, utilities, depreciation, etc.  Strategic forecasts include these operating components but at a much higher level (usually not at an individual department level). Strategic forecasts are mostly account-based and include several components that are typically not in an operational forecast like debt schedules, debt covenants, capital structure changes, treasury assumptions, mergers and acquisitions, etc.

Taking an operating forecast and converting it to a strategic forecast (or vice versa) is not an easy task by any means. So, how can you integrate and build a consolidated approach? Based on our numerous years of experience, the following stages provide an enterprise-wide approach that we feel fits well:

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Performance Architects has been fortunate to design and build a similar approach for many of our clients:

  • Stage 1. Design an account structure that models financial statements in the way the business is actually run (this should not depend on where or how Actuals are reported)
  • Stage 2. Build a strategic model that incorporates all inputs, assumptions and drivers from all the stakeholders across the enterprise
  • Stage 3. Use the strategic forecasts output to create baseline targets at the operational level (department, project, etc.)
  • Stage 4. Build an operational model/forecast
  • Stage 5. Validate operational plans against Actuals data
  • Stage 6. Based on the analysis and comparisons from Stage 5, either change the way Actuals are coded/reported and sync up with the way the business views and runs the unit or change the way strategic forecasts are modeled by updating the account structures or methodologies on the strategic side. This tug-of-war will end up synchronizing and bringing your operational and strategic models one step closer.

You can use a combination of tools like Oracle Hyperion Strategic Finance (HSF) for strategic forecasting and Oracle Hyperion Planning for operational forecasting to achieve the above multi-staged approach to enterprise planning. Once you design and implement such a solution, the intent is not necessarily to have a clear-cut winner in the ensuing tug-of-war but to ensure that you unlock the full potential of enterprise-wide planning without compromising either the operational or strategic plans. In addition, you will also be able to unlock better analytics from your performance management applications.

Author: Sree Kumar, Performance Architects


© Performance Architects, Inc. and Performance Architects Blog, 2006 - present. Unauthorized use and/or duplication of this material without express and written permission from this blog's author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Performance Architects, Inc. and Performance Architects Blog with appropriate and specific direction to the original content.

Put Down That Eight Ball and Pick Up Predictive Planning

December 17, 2014

Introduction

Within the past few years, Oracle developed a simplified version of Crystal Ball to integrate predictive analytics with Oracle Hyperion Planning. The software that makes everything tick is an Excel add-on called “Predictive Planning.” In short, Predictive Planning gives existing Hyperion Planning users the ability to automatically create forecasts and to perform predictive analytics based on historical actual data. In addition to creating base predictions, the system can also create worst and best case scenarios to provide more of a range estimate. For each of these predictions, data can be used at the bottom level, top level, or all levels to give more flexibility to the users.

General Use

In order to access Predictive Planning, a business user must go through a Hyperion Planning web form that meets the necessary requirements. However, these restrictions will generally only have a negative effect on a minority of data forms. For the most part, data forms following common practices (time in columns, accounts/entities in the row) will fit the necessary requirements.  The ability to easily use Predictive Planning on existing data forms is very important because it turns Predictive Planning into more of a “plug and play” style of software.

Aside from the data form layout, the most important components are the different statistical options. While a knowledge of statistics is not completely necessary, it can be helpful. Predictive Planning only requires the business user to choose the items, and then the process automatically finds the best statistical fit.

When running the prediction, there are three methods to choose from (all can be chosen):

– Nonseasonal (required to be selected)
– Seasonal
ARIMA (Autoregressive integrated moving average)

For error measurement, one of the following is selected:

RMSE (Root mean squared error)
MAD (Mean absolute deviation)
MAPE (Mean absolute percentage error)

For a more elaborate explanation on the specific statistical methods used, refer to the guide http://docs.oracle.com/cd/E40248_01/epm.1112/cb_pred_plan_user.pdf  starting on page 41.

The final major component of the prediction set up is the confidence interval. By default, this is set to be 2.5% and 97.5%. At its default, it will create three predictions: Base, Worst Case, and Best Case. For Revenue, the 2.5% represents both the lower boundry and the worst case. Meanwhile, the 97.5% represents the upper boundry and best case. In general, this means that 95% of the time, the prediction falls within these boundaries. The system automatically handles the lower/upper boundaries for Expense and Revenue, flipping them accordingly. For example, the best case for Revenue will be the higher number (upper boundary), but the best case for Expense will appear as the lower number (lower boundary).

Analytic Examples

After a prediction is created, results can be pasted into an available scenario (assuming the user has access to submit data) and/or analyzed from a graph or table. In addition, a report can be created to give some insight into how the prediction was processed. See examples below.

Sample graph comparing historical and forecast data:

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Data table showing the calculated Worst Case, Base Case, and Best Case for each Month-Year:

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After creating a report, the top three statistical methods are shown along with the one that was selected. In this example, the ARIMA method was selected with the highest accuracy. All of the most accurate results are based on “Seasonal,” since the system detected a seasonal presence within the data structure. If I had been expecting something different, I could change the error measurement type to be either RMSE or MAD to see different results. In addition, I could uncheck “ARIMA”  and/or Seasonal as options.

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Conclusion

The information in this blog just touchs the surface of Predictive Planning’s capabilities. For example, data forms often require the inclusion of a prior year’s actual data in order to perform the forecast based on previous data. As we have seen throughout this blog, we can speed up steps by automating that prediction based on actual data.

However, one thing to keep in mind with Predictive Planning is the creation of the Worst Case/Best Case scenarios. These values show statistical highs and lows, but they may not necessarily reflect best/worst case situations that would be based off of items such as economic trends and acquisitions. For more detail in this field, a tool like Oracle Hyperion Strategic Finance (HSF) would be beneficial.

With that said, Predictive Planning is a great tool for accomplishing what it is meant to do: providing on-demand predictive analytics for individual business users.  In addition, business users can use a hybrid method of pasting prediction results into base case forecasts and then overriding the results where necessary. This gives the business user the ability to quickly create the foundation of the forecast, and then to focus on more specific issues. As with all Oracle EPM (Hyperion) components, the primary goal is to increase efficiency in the budgeting process, and there is no doubt that Predictive Planning follows that mindset as well.

Author: Tyler Feddersen, Performance Architects


© Performance Architects, Inc. and Performance Architects Blog, 2006 - present. Unauthorized use and/or duplication of this material without express and written permission from this blog's author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Performance Architects, Inc. and Performance Architects Blog with appropriate and specific direction to the original content.

The Shift to the Cloud: A Recap of Oracle CloudWorld Boston

December 12, 2014

Earlier this week I had the pleasure of attending Oracle CloudWorld in Boston. Besides the monsoon-like weather, it was a great day and an interesting event. As the Inside Sales and Marketing Manager for Performance Architects, I wasn’t really attending the event to learn about the technical aspects of Oracle’s products, but to learn more about Oracle’s journey to the cloud.

I sat in on several business-focused sessions, and I was excited to hear plans for the upcoming year. The first sessions I sat in on were led by Abbie Lundberg from Lundberg Media and Jeff Henley, Vice Chairman, Board of Directors, Oracle. Both Abbie and Jeff were in agreement on how important it is for a company to be able to respond to the needs of their customers and a shift to the cloud will surely allow that to happen. For example, when the IT team spends the majority of their time on maintenance and day-to-day operations, what room does that leave for innovation? For responsiveness? For growth?  Imagine not having to perform another major upgrade or patch update. When companies use software-as-a-service (SaaS), the IT team is freed from these responsibilities.

Freeing IT up to innovate, however, is not the only challenge they discussed. As the current generation of executives retires, companies are left with new managers, new talent, and leadership who are not only accustomed to making business decisions, but who are also accustomed to making – and who are prepared to make – IT decisions.

This leads to another common theme heard at the event: “modernizing IT.”  According to Jeff, the shift to the cloud and the movement to a modern IT infrastructure have to be led from the top of an organization. Leadership has to commit to the shift and to lead the company in the transformation.  And while the shift to cloud for large enterprise companies might be 10-15 years out, smaller and mid-size companies are almost all cloud already.

When you hear “cloud,” Oracle wants you to think of Oracle as a viable option. I was happy to hear Jeff say “Our products haven’t really changed…it’s just that we are offering them as software-as-a-service now.” When Abbie asked Jeff what he thought when managers and employees are ready for the cloud – but top leadership is not – he gave the room a good chuckle when he said, “I think it’s hard. I think it’s difficult…you might end up with a new CEO…”

I also sat in on a presentation on business analytics in the cloud by Sameer Singhal, Oracle’s Consulting Practice Director for Commercial Analytics. The major drive to business analytics in the cloud is that business users want access to data on their own and they don’t want to have to wait days or weeks to access valuable reports that IT has to create. Sounds pretty impressive, doesn’t it? You aren’t the only one who thinks so. Sameer mentioned that Gartner ’s SaaS research demonstrates that 30% of organizations have considered a cloud deployment over the last five years, and that 46% of organizations will have considered a cloud deployment by 2015. Knowing that cloud data centers are, on average, four times faster than on premise data centers, how can you not consider the cloud option?

Not everyone will make the shift, but we are ready if you decide to make the leap. Considering Performance Architects’ recent announcement about our achievement of the Oracle BI Cloud Service Specialization, I would say we are right on pace with the changing market. Overall, it was a great event hosted by a diverse group of talented individuals, and we can’t wait to see what 2015 has in store.

For more information on Oracle Cloud Services please feel free to contact us: info@performancearchitects.com.

We are also hosting a great webinar on this topic next month: Oracle’s Business Intelligence Cloud Service (BICS) Overview and Demonstration.

Author: Melanie Mathews, Performance Architects


© Performance Architects, Inc. and Performance Architects Blog, 2006 - present. Unauthorized use and/or duplication of this material without express and written permission from this blog's author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Performance Architects, Inc. and Performance Architects Blog with appropriate and specific direction to the original content.

Why You Should Consider a Software-as-a-Service (SaaS) BI Solution

December 10, 2014

2014 shaped up to be the tipping point for business intelligence (BI) solutions offered in a software-as-a-service (SaaS) model. Although SaaS BI only accounted for 3% of software revenue in 2013, by 2016 one out of every four new BI initiatives will include SaaS deployments, according to a recent Gartner analysis (Gartner, 2014). We’re seeing not only big-name BI providers such as SAP, MicroStrategy, Oracle, and others turning to SaaS models, but also an emergence of new companies like Birst and BIME whose primary delivery model is SaaS.

Traditional on premise BI solutions are familiar to us all.  With the proliferation of SaaS BI options, new contrasts are created that separate the two, highlight the advantages of each, and provide us a better understanding of which choice is best for a given situation. While there are many benefits to SaaS BI, I chose what I consider to be the main drivers of why you should be seriously considering a SaaS BI solution.

  • Rapid Implementation.  An on premise implementation can take 12+ months. Most BI SaaS providers quote implementation times around eight weeks. With a SaaS BI solution, the days of procuring infrastructure, setting up an environment, and deploying the BI application are gone. This allows you to hit the ground running and also saves future time dedicated to updates of your hardware and software, which is continuously done on the back end by providers.
  • Affordability and Cost Savings.  Saving money on the costs of maintaining hardware and software means a faster return on investment. A reduction in implementation costs, combined with some capital expenditures converted to operational expenditures, results in a lower total cost of ownership. In addition to this, pricing models for SaaS BI offer flexible payment options. This has helped usher many small-to-mid-market businesses into the BI arena.
  • Flexibility and Scalability.  Flexibility refers to the capability to match service capacity to the ever-changing needs of business users, and also the ability to choose from a multitude of SaaS BI deployment models. In terms of scalability, one of the best perks of cloud-based services is that resources are adjustable and can be scaled up or down quite easily when needed.
  • Ease of Use. When running a SaaS BI application, users can access the solution from their laptops, mobile devices, tablets, and (with the direction technology is heading, perhaps someday soon!) on their smart watches! These kinds of products allow you to have browser-based access and control. Any administration settings or issues are handled by the service provider without any effect to the users. This allows you to focus your time more efficiently and more effectively.

Overall, there are many good reasons why you should choose either an on premise or a SaaS solution. As these BI SaaS solutions grow and mature, I’m sure the differences between the two will become more clearly defined. For right now, what we know is that SaaS BI has arrived and deserves to be considered.

Author: John Callaio, Performance Architects


© Performance Architects, Inc. and Performance Architects Blog, 2006 - present. Unauthorized use and/or duplication of this material without express and written permission from this blog's author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Performance Architects, Inc. and Performance Architects Blog with appropriate and specific direction to the original content.

Oracle Hyperion Profitability and Cost Management (HPCM): Goodbye Black Box!

December 3, 2014

Oracle Hyperion Profitability and Cost Management (HPCM) is an Oracle enterprise performance management (EPM or Hyperion) application that allows users to understand the true cost and profitability drivers within their business.  HPCM offers many interesting capabilities, chief among them the tool’s functionality that provides visibility into allocation models.  I’d like to highlight three features in particular that help facilitate this visibility do: “Stages,” “Stage Balancing,” and “Trace Allocations.” Each of these components helps users to easily visualize and comprehend the allocation process while ensuring completeness and confidence in the allocation model.  Say goodbye to the “black box” of old cost and profitability solutions!

1.    Stages

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Within HPCM, stage structures represent the allocation steps within an organization.  With a limit of nine stages per model (all having the ability to leverage multiple dimensions within each stage), allocation designers have a decent amount of wiggle room with which to operate.  Most any account, activity, process, or grouping can be defined in a stage.  Data in the stages will move sequentially per the model.  The calculated results of one stage become the source of the next stage.  While users cannot see driver detail and assignments in this panel, this is a great way to view an application model at a high level to understand the sequential flow of data.

2.    Stage Balancing

The “Stage Balancing” feature allows users to validate their allocation model results after a calculation has been run.  This is the data level validation step that shows not only that the money is flowing, but that it is flowing as expected.  In this manner, Stage Balancing is akin to doing a checkbook ledger-like reconciliation of the data as it moves through each stage.  Input values, assigned values, and unassigned values can be viewed at both the cost and revenue layer.

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If the numbers don’t add up in this validation, one great highlight of the Stage Balancing panel is direct links via Oracle Smart View for Office (Smart View) into the Oracle Essbase database (the database underlying HPCM that comes bundled with the solution).  Smart View interfaces with Microsoft Office products and allows users to access data.  When a business user clicks on a link, this gives them a view of their model data at the correct point of view.  This is a great benefit, as it gets business users to the value without having to worry about the specific dimension combinations needed to arrive there.  This integration allows the user to avoid having to build expertise in both Smart View and in HPCM’s outline and dimensionality.

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3.    Trace Allocations

The Trace Allocations feature allows users to visually follow the flow of funds through an allocation model from start to finish.  This screen brings the idea of “linked data” to life.  Users can drill forwards and backwards to visually follow money from source to destination, as well as the intermediate steps it took along its way.  The ability to audit where the money came from and where it went to differentiates HPCM from your general ledger, an Excel worksheet, or even Essbase.  While HPCM keeps much of its complicated outline hidden from the user, it provides full transparency in the area needed most – the flow of data.

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The Trace Allocation feature also offers an “Accompanying Properties” section (pictured in the screenshot below in red).   Highlighting a link in the visual aid will display source, allocation, and destination detail.  Business users can see the total received and moved by a particular data source/destination from all points.  This also includes the name of the driver and driver value used to move the data.  Business users can examine how much money was moved from point to point, and perhaps most importantly, be able to show how.   Such an open process within HPCM changes the conversation to analyzing drivers and allocation methods, as opposed to questioning the validity of the numbers and process.

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Author: Joseph Francis, Performance Architects


© Performance Architects, Inc. and Performance Architects Blog, 2006 - present. Unauthorized use and/or duplication of this material without express and written permission from this blog's author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Performance Architects, Inc. and Performance Architects Blog with appropriate and specific direction to the original content.