ACG Business Analytics Blog

Trends in Enterprise Performance Management...

Posted by Rob Harag on Sun, Jun, 07, 2015 @ 06:13 PM

Enterprise Performance Management (EPM) systems are becoming more powerful, user friendly and more accessible - that is the core theme of an article published recently by CFO Magazine. Advances in technology allow EPM systems to process larger quantity of data on-demand and thus increase their analytical capabilities. Wider choice of specialized products and new features such as compatibility with Excel, predictive analytics, cloud computing or mobile access are transforming the way users interact with the applications and thus help advance many traditional functions and business processes.

While IBM, SAP and Oracle command about 70% of the market, there are plenty of sophisticated systems to choose from in the remaining 30%. Reversing a prior trend of industry consolidation, more companies are entering the market and provide interesting capabilities that are often tailored to a specific market or industry segment. Examples of such focus areas include budgeting, forecasting, profitability optimization or scenario modeling.

Gartner categorizes EPM solutions into two main buckets: Office of Finance Processes and Strategy Processes. Most of today's solutions, however, aim to combine financial and operational data across the company and provide a fully integrated view of the company's performance. Such increased transparency and insight into underlying trends and drivers facilitates a higher focus on key factors affecting financial performance. This in turn helps to more effectively execute a company's business strategy.

There are three primary drivers that are currently changing the way people and companies interact with and deploy EPM solutions:

Speed – with the increased use of in-memory computing, systems are more nimble and flexible to complete calculations in real time and are able to handle the ever increasing quantity of data. The improved performance facilitates a number of benefits such as usability, collaboration, integration and others. These capabilities are further changing the role of Finance and help it to be a more effective facilitator of change, trusted advisor to the business and a driver of value.

Usability – there have been great advances in user friendliness and usability of the tools as vendors continue to make significant investments into more intuitive and easier to understand user interfaces. Dashboarding, visualization, integration with Excel, web-based capabilities and templates are some of the key focus areas. Cloud computing plays an important part in increasing adoption through better flexibility of use. Finally, mobile computing facilitates more distributed data collection and reporting with the ability to drill down directly on the mobile device, typically an iPad.

Integration – EPM systems are becoming increasingly more integrated with solutions expanding far beyond the traditional financial planning and reporting. Operational planning, sales performance management, strategic planning are only a few examples of such new use cases. Integration of these systems and processes provides a higher quality output and facilitates collaboration across groups and departments, which yields more efficiency and improves performance. Predictive Analytics, while still in early stages, is further pushing the frontier on the type of insight and depth included in financial information involved in decision-making.

Topics: Business Forecasting, Performance Management, Financial Planning and Analysis

4 Reasons Why Financial Planning & Analysis Is Not Effective

Posted by Rob Harag on Fri, May, 01, 2015 @ 09:40 AM

Considering how important the Financial Planning and Analysis (FP&A) function is in providing critical business insight to company CFOs and CEOs, it is surprising how low its capabilities are still regarded amongst business executives. According to a recent study published by APQC, only 40% of 130 executives surveyed described the FP&A function as effective. Given all the talk and focus in the industry on business analytics and insight, as well as the availability of numerous systems and solutions from niche players and mainstream vendors, it is surprising that the FP&A function is still rated this low. Based on our observation and experience, there are four primary factors that drive this outcome:

1. Continuously raising the bar on expectations

The demand for meaningful business insight and analysis has been growing continually over the past years. Economic uncertainty, regulatory scrutiny, increasing competition, changing weather patterns or geopolitical pressures keep creating new and more urgent demand for information that FP&A needs to satisfy. Even as the FP&A capabilities, processes and technology improve, the FP&A groups are under increasing pressure to respond to more and more ad-hoc requests from many different groups and stakeholders. As a result, they spend most of their time scrambling to respond to requests under rapid fire and often do not have the ability to step back and develop capabilities that would bring them to the next level. What was working well yesterday is not good enough today.

2. Playing catch-up with technology

Today’s finance and planning infrastructure is typically complex as a result of aggressive growth and multiple mergers and acquisitions. Often times the reporting and analytics relies on information from multiple legacy or department level systems. Excel typically plays a significant role in arriving at the end product. To further complicate matters, the demand for business driver detail and modeling require information residing in transactional systems that are outside finance. Even though companies continue to invest and integrate the various systems, ongoing business evolution continues to fuel more changes at a rapid pace, thus creating a moving target. As a result, Finance spends most time pulling information together from various systems and compiling reports or explaining variances at a high level (vs budget) rather than analyzing data and providing value add insight.

3. Slowly adopting advanced planning techniques

Majority of companies still rely on a fairly static process for budgeting, forecasting and reporting. While some of the advanced techniques such as rolling forecast or driver based planning are slowly creeping in, they are not the prevailing methodology yet. It is not uncommon for a large organization to spend 6 months preparing the annual budget and for the budget to be obsolete shortly after it has been completed. Forecast is often times the result of a finance process (YTD Actuals plus Budget) and includes little real time insight from the business. Reporting tends to be backward looking, focused on results to-date and explaining variances to plan or forecast. As such, financial planning is not sufficiently flexible and aligned with business strategy and is slow to adapt and accommodate changes in business conditions.

4. Advanced Analytics still in early stages

While predictive analytics, demand planning and other capabilities are all the buzz these days, they are at a very early stage of adoption. Even if they exist, they are typically not integrated with the overall financial performance management framework. They are usually performed by a dedicated group of people, many times statisticians or other similar functions, in isolation and focused on a specific area / problem. The result is then used as an input into the planning process for further processing. Tremendous upside exists in integrating the forward looking capabilities into financial planning from both systems and procedural perspective, however it will take some time until this practice becomes mainstream.

Topics: Business Forecasting

Should I be Developing TM1 Applications Using Performance Modeler?

Posted by Jim Wood on Wed, Jun, 04, 2014 @ 12:44 PM

Performance ModelerBefore the advent of IBM Cognos TM1 10 any company or individual looking to complete development within TM1 used the tried and tested but dated and unhelpful development tool sets. When IBM introduced TM1 10 back in 2011, they introduced a whole new, web based development tool set called Performance Modeler. This partnered with the rebranding of what was previously known as Contributor (now known as Application Server) introduced a new development tool partnership that wasn’t just IBM trying to bring new options in to play, it was the introduction of whole new development and deployment methodology. This new methodology is based around using the Application Web portal as the front end for gathering and reporting on planning information with Performance Modeler used to get you there.

With any new methodology there is always a level resistance to it, and this was the case within the current TM1 community. While the old tool set was not the best, it was very well known. We have seen recently however, with IBM pursuing this methodology that more and more people, especially those new to TM1 are following IBM’s new pathway. So with more people starting to use Performance Modeler and with IBM continuing to develop it further, all TM1 users / developers need to start looking at it as a serious project implementation option.

So the question has to be: should you be looking to use Performance Modeler?

Performance Modeler is easy to use.

Performance Modeler has plenty of new wizards built in to make previously difficult tasks a lot easier. There is a built in wizard (called guided import) for building cubes, dimensions and even for importing data. Adding calculations has been made much easier. On top of making calculations easier to build IBM has also added many new functions to Performance Modeler, a perfect example of this is the Lag function that makes building time based balances easier to build and maintain.

Performance Modeler makes building Process Workflow easy.

With its perfect partnership with Application Server, Performance Modeler makes building the parts required for a Workflow implementation easier. Within Performance Modeler you can create the required hierarchy for managing your workflow and it also handles dimensions differently so that any cube built is optimized to work well within the workflow framework.

Performance Modeler offers you a range of new options.

Performance Modeler has added development options that were not possible using the old tool sets. For example removing a dimension from within a cube is now a simple drag and drop task. Previously this would have involved rebuilding the cube.

Performance Modeler is the way forward.

Performance Modeler is a key part of the IBM Cognos TM1 development road map. IBM see this new development methodology as a key part of making TM1 an integral part of their FP&A strategy going forward. As it progresses, more features and improvements will be added.

Now that we’re past the early development stages it’s an ideal time to take a look at performance modeler and see what benefits it can bring to you.

Topics: IBM Cognos TM1, Business Forecasting, Performance Modeler

How Do TM1 Financial Systems Ensure Clean Data?

Posted by Peter Edwards on Wed, Jan, 08, 2014 @ 03:44 PM

Summary

Almost half of new business initiatives fail because of poor data, according to a recent article on the EPM Channel website. While manual processes can temporarily fix issues, The IBM TM1 technology uses a series of checks and balances to ensure that businesses can build a database on clean data, saving employees time and avoiding costly mistakes.

How Do TM1 Financial Systems Ensure Clean Data?

Almost half of new business initiatives fail because of poor data, according to a recent article on the EPM Channel website. This trend fuels mistakes in everything from bill payments to shipping, and often means that your best employees spend more time organizing data instead of analyzing it.

ibm_cognos_tm1This is a long-standing pain a lot of businesses incur with dirty data. With Big Data, businesses have large amounts of data, so the quality of that comes into question. Organizations often are looking at ways to improve their data because they have too many manual processes in place or their data is being cleaned in a non-automated fashion. If your data is clean and organized, you’ll streamline processes and align the organization on a set of numbers. As the EPM Channel article points out, it’s best to do this at the start, saving employee resources and avoiding costly problems.

There are systems that can help. TM1 financial solutions enforce what’s called referential integrity in data. Many times, when pulling data to put into TM1, there are problems in supporting systems that must be fixed. For instance, if you’re pulling data from a financial system that’s doing consolidations, there could be numbers at an account level that do not necessarily total to the parent account that they should roll up into. That’s because the system allows users to store two different numbers. This means there are a number of child accounts that fail to add up to the appropriate total because the database doesn’t enforce referential integrity.

Most relational databases or ERP applications don’t necessarily enforce these rules. They try to put business rules in place, but fundamentally the technology allows users to enter data in different places, creating conflicting information. When pulling data into the TM1 financial systems software, the detail-level account data rolls up into the parent account, creating that figure. This method ensures that the parent figure isn’t entered separately and avoids any situations where the child accounts don’t add up to the parent number. Therefore, users who leverage TM1 as there database are much more likely to have quality, clean data.

To learn more about TM1 financial solutions or see a TM1 demo contact ACG.

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Topics: IBM Cognos TM1, TM1 Technology, Clean Data, Performance Management, Business Forecasting

4 Ways IBM Cognos TM1 BI Solution Can Cure Forecasting Problems

Posted by Peter Edwards on Mon, Nov, 18, 2013 @ 03:45 PM

IBM business cognos tm1 forecasting rf

Summary

Does your company suffer from common forecasting problems? In a white paper on the subject, the IBM Beyond Budgeting Round Table illustrates how the IBM Cognos TM1 business intelligence solution can help finance managers identify common symptoms and implement solutions that lead to a healthier organization.

Whether companies realize it or not, they likely suffer from at least one symptom of forecasting illness. Misconceptions and antiquated forecasting processes lead to decreased accuracy, quality and profitability for businesses. To successfully treat these forecasting illnesses, finance managers must identify common symptoms and implement solutions that lead to a healthier organization.

In a white paper titled “Seven Symptoms of Forecasting Illness” the IBM Beyond Budgeting Round Table illustrates how the IBM Cognos TM1 business intelligence solution can help identify and cure these pervasive ailments. Here are three of the top forecasting issues with a bonus issue that the ACGI experts often see.

1) Semantic confusion: A company might show signs of semantic confusion if the organization finds it difficult to deal with unexpected or undesirable forecasts. This symptom can manifest as a blurred line between the forecast and the company’s goal.
Cure: To address this symptom, companies can use the IBM Cognos TM1 business intelligence solution to allow managers to create, maintain, and reference multiple forecast scenarios easily and efficiently.

2)  Visual impairment: A company may suffer from visual impairment if it is obsessed with the year-end forecast numbers, or if it is surprised by new developments at the beginning of the fiscal year.
Cure: Companies should focus on building a comprehensive company forecast strategy. BP is a great example of the power of combined forecasting. BP brought all of the company’s stakeholders together in a large auditorium and efficiently completed a comprehensive company forecast.

In some companies, salespeople are either pushing their numbers to count toward next year’s sales goals or holding their numbers to this year to benefit themselves under their compensation plans. You really need to separate compensation from the forecasting process to take this manipulation out of the process and get truer information.

3) Lack of coordination: If an organization has multiple sources, or silos, of data, it can’t create reliable, consistent forecasts.
Cure: In order to have a good forecasting process, you also need good data organization in the company. This can be achieved by adopting a single forecasting system throughout the entire organization and feeding data into the forecasting system from other enterprise systems like the General Ledger or the Human Resource Management systems.

4)  Lack of executive sponsorship: If individual departments are attempting to improve the forecasting process, but others are split over the importance of the task, an organization may suffer from a lack of executive sponsorship.
Cure: In order for a company to be successful in their financial planning and reporting efforts, it has to come from the top down. These processes will touch multiple parts of the organization and must be designated a key strategic initiative of the entire company in order for it to be successful.

All companies suffer from at least one type of forecasting illness. These factors are a reminder that every business needs to constantly examine its core process and culture to ensure they’re using the most accurate forecasting process and tools. By implementing a data analysis tool like the IBM Cognos TM1 business intelligence solution, organizations can achieve a high level of efficiency and promote healthier forecasting.

To learn more about these and other key forecasting issues companies are facing, download the white paper, “Seven Symptoms of Forecasting Illness.”

 

Free Whitepaper: 7 Symptoms of  Forecasting Illness

Topics: IBM Cognos TM1, Performance Management, Business Forecasting

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