Make  Decisions That Count

Good managers focus on developing and implementing successful strategies. They don’t take high performance for granted. They ask the right questions, test the best ideas, and make only those decisions that are proven to improve the bottom line.

Testing and adopting the best ideas is dependent on use of performance tools and the quality of the analysis using these tools.  Some organizations lack a culture and tradition of fact-based analysis and decision making. Others rely on outmoded approaches to decision making that are inaccurate and may result in missed opportunities or decisions that appear profitable but in reality reduce the bottom line. Our experience shows that the “profit gap” left on the decision table is 400% or more of current profits.

The Five Steps to Profitable Decisions

1.      Identify the top sources of increased profits

The first step is to identify the biggest potential sources of increased profit. These are the areas where good decisions count. Specific areas for each company will vary depending on the nature of the business, current business performance, competitive conditions, and the strategic direction of the business. They include lines of business, market segments, channels of distribution, customers, product mix, pricing, marketing initiatives and buckets of cost.

In some cases the areas of greatest decision impact will be easy to identify. High level analysis of current performance versus strategic goals will find some obvious targets. This analysis can be done very quickly. If information is required to pinpoint action areas, more analysis is necessary. This additional analysis will reveal hidden opportunities to increase profits. For example, a high level profitability model can reveal market segments that are destroying profits. This profitability model can be built in 60-90 days and may lead to immediate decisions that increase profits.

2.      Evaluate how decisions are made

Effective decision making is dependent on the sources of decision information and the ease of making decisions using this information. It is heavily influenced by the use of performance measures to guide and reward decisions.

If the primary (or exclusive) source of financial information is the accounting system, decisions will likely result in significant profit destruction. This is because the primary purpose of an accounting system is financial reporting. Accounting was not designed to provide information about the sources of profits. Here are some examples of the negative impact on decisions:

• Decisions on product and service mix and price are affected by inaccurate and incomplete product costs. This is because manufacturing companies use standard costs as the measure of product cost, and standard costs are notoriously inaccurate. Service companies are not required by generally accepted accounting principles to have product costs, so often have no cost measures to use in decision making. 
• Except in aggregate, financial systems do not report the cost of market facing activities such as customer acquisition, advertising and channel support costs. Decisions regarding market segments, channels and customers therefore lack relevant cost information. Customer relationship management (CRM) systems include lots of information about customers, but usually do not report the cost to serve each customer or customer group. 
• Financial systems report cost by account by not by process or objective. Accounts—such as depreciation, salaries, office supplies etc.—provide no information about the state of the underlying business purpose. If salaries are decreased in an effort to improve profits, will this benefit the business or hurt the business? Does spending contribute to the accomplishment of strategic objectives? It is not possible to answer these questions using cost information from the financial system.

The ease of making decisions is dependent on the availability of decision tools and timely access to decision information. For example, in a company with several distribution centers, an important decision is the choice of the distribution center to serve a particular customer. This complex decision may involve manufacturing costs, shipping costs, material handling costs, taxes and tariffs, and the costs of meeting customer requirements. In the absence of an optimization model that takes each of these cost elements into account and determines the correct solution, it will be difficult if not impossible to determine the lowest cost alternative.

Difficulty obtaining information can have a negative impact on decisions. Relying on out-of-date information in a rapidly changing business environment may result in the wrong decision. Delays obtaining information will lengthen the time it takes to make a decision, increased analytic effort will increase cost, and decisions may be made by necessity without the insights derived from the information.

3.      Close the decision gap

Closing the decision gap, and focusing decision outcomes on profit improvement, requires ready access to decision relevant information and tools. Such a system typically includes cost and profitability management models, decision analysis and optimization tools, and desk top access to up-to-date relevant information and tools. 

Cost and profitability models are designed to report the exact information needed to make critical profit enhancing decisions. They differ from financial accounting by their use of activity-based costing (ABC) modeling techniques and scope of analysis. They also leverage the billions of transactions in computer systems to create a rich repository of cost and profit information. When fully automated using data integration tools, these models allow decision makers to focus their time on decision analysis rather than data entry and spreadsheet manipulation

Decision analysis and optimization tools help decision makers derive meaning from the information in the cost and profitability models, and determine the decision outcomes with the highest likely profitability.  For example, using analytics it is possible to determine which customers are the most profitable over an extended period of time and when adjusted for risk. Based on this analysis, marketing initiatives for customer acquisition and retention and up sell can be targeted to these profitable customer groups.

Desk top access to decision relevant information and tools increases the impact of decisions on profitability. In such a system each decision maker uses a portal to access the information he or she needs for decision making. Standard reports, refreshed to reflect the most recent information, are supplemented by queries into the profit information data bases to combine and report specific types of information. Projections of profitability, pricing models, cost minimization and other optimization techniques are available as needed from the portal.

4.      Change the performance measurement system

In a perfect world managers would automatically change their approach to making decisions based on the availability of information about the sources of profitability and use of decision making tools. In reality, lack of enthusiasm for analytic approaches and inappropriate measurements may be barriers to adoption and execution.

Analytic approaches to decisions that focus on profitability benefit from management commitment. Sometimes this comes down to culture—some organizations are immersed in fact-based decision making, while others follow a more intuitive approach. If top management incorporates analysis in key decisions, it is likely that the rest of the organization will follow their example.

The availability of information about the sources of profitability will not be enough if managers are evaluated and rewarded based on non-profit measurements.  For example, one company implemented a profitability management system but found that sales did not use the system to determine what to sell and how to price the product. This was because the sales force was compensated based on sales revenue.  A change to compensation based on net profit margins saw an immediate response, with product mix changing dramatically in the month following the change.

Adding objectives and measures of profitability to scorecards is a great way to focus attention on making profitable decisions. In a balanced scorecard, measures of customer, segment and channel profitability can be added to the customer dimension. Measures of cost can be added to the process dimension to focus cost improvement efforts. The balanced scorecard also helps focus decisions on improving long-term profitability rather than actions that favor short term profits.

5.      Track the results

It is important to measure the success of profitability management. Tracking results reinforces the emphasis on fact-based decision making and the positive impact of decisions on the bottom line. It also encourages improvements to the profitability management system to strengthen the program.

While it may not be possible to track the impact of every decision, it is feasible to measure the success of the key profit initiatives that account for 80% or more of the improvements in profitability. What was the increase in segment profits resulting from a new negotiating strategy using accurate measures of customer profitability? What was the return from investing in customer retention activities? What were the cost savings from replacing vehicles in the fleet based on minimizing the lifetime cost of equipment ownership? The returns from these and other initiatives can be accumulated to provide an overall measure of success of profitability management. For most companies the return will be significant.

Conclusion

Twenty five years of research and implementation of profitability management systems confirms that many companies have hidden pockets of unprofitability and profit opportunity. With the right information and tools, and systems to support and motivate profitable decision making, it is possible to increase profits by 400% or more. This increase is derived from making smarter decisions. It is possible without the heavy lifting and cost associated with initiatives to increase sales or reduce costs.

There are five proven steps to smarter and more profitable decisions. The first step is to understand where the profit increases will comes from and focus efforts on those areas. The second step is to assess how decisions are made and identify gaps in the type of information and tools that are used to make decisions. The third step is to implement a profitability management system that makes it possible and easy for managers to find and exploit the hidden opportunities to increase profits. The fourth step is to bring the performance measurement system into line with the new emphasis on profitable decisions, providing managers the motivation to make decisions that increase the long-term profitability of the company. The fifth and final step is to score the results of the new profitability management system and decision emphasis. This reinforces the success of the program and provides impetus to continue and improve profitability management.

Maybe this is not surprising, but it is certainly disappointing. Many budgeting systems are dysfunctional and create plans that are inaccurate and out-of-date before the ink is dry. They are strategically irrelevant, inflexible, and disconnected from operational reality. To say that managers do not enjoy or value the budget process is an understatement.

For those of us who are committed to the benefits of performance management, this is tough medicine to swallow. If budgeting is dysfunctional and so many people recognize it to be so, why is it so difficult to fix?

Let me take a stab at answering this question. Most of the methods referenced above focus on the effectiveness of the budgeting process. Are budgeted costs an accurate reflection of strategy, sales volume and mix, and process performance? Does the planned level of each type of resource reflect the likely demands on these resources? If you make a change to the efficiency of the process, is it easy to estimate the impact on budgeted costs?

These are important analytic questions, but it is difficult to answer them until a more fundamental question is answered. Is the current budgeting process reasonably efficient? Our experience suggests that budgeting processes are often highly inefficient and not susceptible to improvement in effectiveness until the inefficiencies have been addressed. 

Take the case of the parts manufacturer. This company prepared a quarterly rolling forecast that projected operational requirements and financial results. The planning process was labor intensive involving as many as 60 people working more than 90 days to complete. Given the need to do manual data entry, maintenance and consolidation of over 4,000 spreadsheets, it was not surprising that the new quarterly forecast started before the forecast for the previous quarter was complete. The process was poorly controlled, error prone and inaccurate.

What was the impact of this forecasting system on the business? There were significant costs associated with the manual process. Forecasts were late and unreliable.  Importantly, the analysts who were buried in data and spreadsheets had no time for analysis. Management could not fine tune their plans to better accommodate known changes and improve earnings. They blamed the forecasting system on their inability to adapt quickly to changes in run rates and product mix from key customers resulting in lower than expected quarterly earnings and reductions in the stock price.

I would argue that this experience prohibited any improvement in the underlying method until the inefficiencies and the high cost of planning were addressed. Importantly, fixing the inefficiencies of the system would free up the time of analysts to focus on cost and performance management rather than data churn and spreadsheet manipulation.

Does your experience support this view? Does your budgeting process lack discipline, accuracy, relevance and responsiveness? Is the inefficiency of the budgeting process the biggest barrier to improvement? If the process were fixed, could you successfully address the issues of relevance and operational responsiveness?

Common Cents, Second Edition, reveals how Activity-Based Costing (ABC) and Activity-Based Management (ABM) can help you make the right decisions about customer and product mix, marketing channels, and performance improvement. Originally written and now revised and updated by ABC/ABM pioneer Dr. Peter Turney, this book walks you through each step of the process, giving you the tools to more accurately identify, assign actual costs to, and report on the elements of each customer, product, or service, increasing your organization’s process efficiency and profitability.

Whatever business you’re in, ABC and ABM can help transform your organization from average to world-class. Common Cents reveals the hidden opportunities to improve profitability or reduce cost, and shows you how to position your resources and direct initiatives to achieve maximum results.

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Activity-based costing has been around since the mid-nineteen eighties.  Given its longevity, it’s worthwhile to answer:

• How has ABC evolved over its life cycle?
• What lessons have been learned from the evolution of ABC?

• What can ABC do today that it could not do 20 years ago?

This article answers these questions by examining the evolution of ABC in the context of a product life cycle.  It summarizes the history of ABC according to the phases of its life cycle, highlights its expanding functionality over time, and details the lessons learned from two decades of use.  It concludes with a description of the current state of ABC as a key input and value adder to performance management systems.

It took just a short time for ABC to be recognized as an innovative and potentially valuable costing methodology; yet it took another 20 years to reach its full potential.  ABC emerged in response to competitive pressures that exposed inaccuracies in cost accounting.  Early uses helped companies view the distortions inherent in cost accounting systems leading to changes in strategy, processes, operations and improved competitive position.

Buoyed by early successes, ABC emerged as a powerful profit analysis tool.  These successes stemmed from ABC’s ability to reveal the hidden sources of profitability and embedded cost, and to serve as a catalyst for decisions to improve profitability.  Over time ABC adapted to new areas such as cost-to-serve activities, customer profitability, channel profitability, and the use of ABC outputs to perform capacity planning and drive predictive modeling.  By the late nineties ABC was used extensively in diverse industry and government sectors.

Today, ABC is the emerging foundation of performance management.  If you lift up the hood of a performance management system, you will find ABC powering performance measures for scorecards, providing rates for customer profitability analytics, helping devise human resource plans, modeling sustainability, and supporting budget development and planning.

Like most technologies, the value of today’s ABC is the result of many years of development and learning.  In assessing its value for your organization, it is important to understand how it has evolved and how this evolution has created opportunities to create value.  Whether you are considering ABC for the first time, or a returning early adopter, it is time to take a fresh look.

THE ABC HYPE CYCLE

The hype cycle is a graphic representation of the maturity, adoption and business application of a technology.  It reflects differences in human attitudes to the technology .  Early in the cycle there is little practical knowledge about the technology, and thus, an organization’s cost/benefit analysis is often dominated by difficult to quantify risk factors making a decision on adoption challenging.  However, as knowledge accumulates risks reduction occurs facilitating more informed judgments regarding adoption.

The hype cycle typically covers the period of time between market introduction and a 30 to 50% adoption by the business community.  The ABC hype cycle has six phases of evolution: (1) technology trigger, (2) peak of inflated expectations, (3) trough of disillusionment, (4) slope of enlightenment, (5) the plateau of productivity, and (6) the post-plateau phase (Figure 1).  The first five phases represent the history of ABC, while the sixth phase is the current state.

Figure 1: The ABC hype cycle.

Technology Trigger (1984-1987) Innovations in Cost Accounting

Discontinuous innovation is generally the result of a trigger – an external impetus that stimulates innovation.  The trigger for ABC was the increasing Japanese competition experienced by western companies, particularly those in the electronics and automotive verticals.  Believed to be the result of low-wage labor and undervalued currencies, they were de facto innovative management practices, such as just-in-time material flow systems, continuous improvement, and statistical process control.

The impact of this change on western companies was dramatic.  Some retreated and complained of unfair competition, and others adopted the management practices used at leading Japanese companies such as Toyota.  A few western companies developed innovative practices of their own, including innovative costing methods.

New approaches to costing emerged in the manufacturing sector.  Companies recognized that the cost accounting systems used at that time had unintended negative strategic and operational consequences.  Tektronix, for example, allocated manufacturing overhead to products based on direct labor.  To reduce measured cost, engineers designed products to use less direct labor.  This gave the appearance of reducing manufacturing overhead.

Although this approach reduced manufacturing and assembly time, it increased the complexity and the number of unique parts in each product.  As a consequence, it increased the cost of purchasing, receiving and stocking thousands of different parts as well as overall cost.  Only when the cost of part related activities was allocated to products based on the number of unique part numbers used in the product was this bias corrected and engineers encouraged to use common parts wherever possible.

Tektronix’ new cost accounting method helped engineers understand the impact of their decisions.  While lacking the accuracy and diagnostic capability of ABC systems, the elimination of the behavioral distortion inherent in the cost accounting system helped Tektronix compete .  Tektronix’s success, along with that of others, was an important step to developing first generation ABC methods.

Peak of Inflated Expectations (1987-1991) First Generation

The peak of inflated expectations is a bubble of enthusiasm for a new technology.  For ABC, the journey to the top of the bubble was accompanied by extensive publicity and the emergence of first generation methods and tools.

Beginning in 1987, a flood of articles on ABC appeared in the Harvard Business Review, Journal of Cost Management and other publications.  Invitations to attend conferences by the Institute for International Research and other organizations filled mail boxes.  These publications and presentations explained how to implement ABC, what it meant, and what impact it would have on businesses that adopted it.

As with most technologies, the combination of interest among potential users and the development of first generation methods encouraged commercial development of the ABC market.  Most of the large consulting firms built ABC practices in the late 80s and early 90s; and the first commercially available software for ABC was introduced in 1990.

Underlying this enthusiasm was the recognition that ABC could yield important insights into profitability. This was because ABC:

• eliminated the product cross subsidies inherent in cost accounting;
• revealed the sources of loss that were responsible for the decline in profitability; and
• acted as a catalyst for decisions improving operational efficiency and profitability.

For example, Figure 2 is for a manufacturing company that believed all of its products were profitable.  An ABC model revealed that over 25% of its products were unprofitable and another 40% were breakeven.  ABC helped the company develop a new focus on profitable markets and customers, pruned unprofitable products, redesigned products to remove cost, and eliminated non-value added activities.  This new focus transformed profitability from “worst in class” to “best in class” .

Figure 2: The ABC “S” Curve.

The lesson learned from this period was that the value of ABC was its ability to drive change.  Early versions of ABC were designed to improve the accuracy of product cost using high level cost pools and cost drivers.  These systems helped management see the profitability of products; however, they had limited diagnostic capabilities.  The inclusion of activity and customer costs during this period increased the diagnostic power of ABC leading to activity-based management (ABM).

Trough of Disillusionment (1991-1995)

The excesses involved in scaling the peak of inflated expectations led inevitably to the bursting of the bubble.  Media over-enthusiasm, confusion over the method itself, limits to the method and supporting systems, difficulties of sustainability, and some well-publicized failures were precursors to lowered expectations.  ABC was also the victim of shifting attention to new management methods.

Critics of ABC generally fell into two camps.  Some argued that ABC was inconsistent with the principles of continuous improvement and total quality management.  They wrote that ABC lacked customer focus, was not process oriented, did not enhance organizational learning, and was top down in approach (i.e., did not involve employees).  Others argued that ABC was inconsistent with the theory of constraints.  A common argument was that ABC could not reliably measure the short-term impact of decisions on operating cost, inventory and throughput.

These criticisms reflected a misunderstanding of the purpose and nature of ABC.  Early versions of ABC were designed to reveal strategic insights into sources of profitability.  The intention of ABC was neither to provide day-to-day guidance on process quality nor to measure short-term variable cost.

A contributing factor to lowered expectations was the relative immaturity of the ABC method combined with lagging systems technology.  In hindsight, it was ambitious to build ABC models using non-enterprise software on PCs.  It was inevitable, with rare exceptions, that ABC models of this era were difficult to build, cumbersome to use, and lacked regular reporting and integration with data sources.

In some cases failure was attributable to poor change management.  For instance, in the case where ABC revealed that 80% of a company’s products were unprofitable, management denial precluded meaningful change.

In other cases failure was the result of incorrect implementation or the design of the model.  One company’s ABC model was so complex it costs exceeded the savings the model indicated were available.

ABC’s gain from media exposure during the climb to the peak turned to loss when management attention turned to other emerging methods.  Interest in ABC declined after 1992 when attention turned to business process reengineering, enterprise resource planning (ERP) systems and the balanced scorecard.

The lesson from this period is that critical commentary, diminished user interest and failure are inevitable byproducts of the development of an immature technology.  The good news is that ABC crossed the chasm of failure and continued its learning and development.

Climbing the Slope of Enlightenment (1995-2000) Second Generation

Climbing the slope of enlightenment was characterized by increased market penetration and continued technology development.  This occurred in spite of the proliferation of ERP systems, which were costly and time consuming initiatives, and the need to bring systems into compliance with the new millennium (Y2K).

Early ABC implementations were focused on correcting the errors in overhead allocation to products inherent in cost accounting systems.  With continued development, however, it was clear that ABC was applicable to areas outside the scope of cost accounting.  These areas included administration, sales, marketing, research and development, supply chain, and logistics.  Figure 3 is an example of ABC analysis of cost-to-serve activities supporting customer profitability analysis.

Figure 3: ABC Profit Cliff.

ABC implementations expanded into insurance, healthcare, packaged goods, energy, banking and other industries.  These industries faced increasing competition during the 90s and benefited from information about the cost of services, customers and activities.  Government agencies and the military used ABC to help ameliorate budget pressures.

The addition of predictive modeling to ABC extended its use from historical costing to resource and capacity planning and scenario analysis.  Predictive ABC models served as factual bases for budgetary cost estimation and scenario analysis for decision making.

Another development involved creating detailed models of business processes.  The process models revealed opportunities for cost reduction, helped prioritize opportunities based on cost, time and quality, and allowed tracking of the impact of improvements on resource capacity.  Cost savings of the magnitude of 10-30% of analyzed cost were achieved routinely across industry sectors .

Plateau of Productivity (2000-2006) Third Generation

The plateau of productivity is where the adoption rate approaches mainstream use of the technology – a market penetration exceeding 30%.  It is the point at which the benefits of the technology are recognized and believed to exceed the cost and effort required to implement.

Market penetration for ABC varies from industry to industry and country to country.  However, there is evidence that penetration rates for ABC have reached the threshold of 30%.  The Gartner Group estimated that between 20 and 50% of global 1000 firms have adopted ABC .  A survey by Business Finance in 2004 indicated that 37% of companies with annual revenues in excess of $1 billion had established ABC programs .  Earlier surveys in the 90s showed increasing adoption rates over time and are consistent with ABC entering the plateau phase in the 2000-2004 timeframe .

Increasing interest in ABC was fueled by several factors.  These included new evidence of financial benefit, emergence of a new generation of enterprise ABC methods and software, and the use of Internet and business intelligence (BI) systems to report current ABC information to decision makers.

Another positive factor was the desire of many organizations to realize a positive return on their systems investments.  These systems met important goals but often did not improve financial performance.  For example, ERP systems effectively integrated transactions but were unable to guide management which products and services to sell, and which customers to serve.  ABC corrected these omissions and revealed opportunities to improve financial performance.

New methods emerged that reduced the cost of implementation and reduced the effort required to maintain ABC systems.  These methods included web-based surveys, time-based algorithms to measure complexity; and the use of extract, transform, and load (ETL) technology to integrate ABC with data sources.  These methods addressed concerns that ABC was useful but overly difficult to implement and maintain.

Improvements in systems technology were important to these developments.  ERP systems and BI tools made it easier to build and modify advanced ABC models and report the information to management.  Enterprise ABC solutions coupled with enterprise level reporting tools were easier to sustain over an extended time frame.

New uses of ABC emerged to increase the value derived from the tool.  These uses included shared services pricing models for IT and other corporate functions to support service level agreements (SLAs) with business units, target costing for product design, optimization of logistics, supply chain and IT investments, minimization of the total cost of ownership of equipment and other assets.

An important lesson from this period is the impact of technology development and cumulative learning on the cost-benefit equation of ABC.  Enhanced functionality and reduced cost opened up entirely new applications for ABC and encouraged early adopters to take another look at this method.

Post Plateau (2006-present) Fourth Generation

The beginning of the post plateau phase coincides with the use of ABC as an integral component of business performance management solutions, including profitability management, performance measurement, financial management, sustainability and human capital management.  

Profitability Management.  New profitability management tools and solutions today relay on ABC information to increase analytic power and accelerate results; and are capable of processing billions of transactions in minutes.  This power allows ABC analysis of complex business models with millions of customers.  For example, a large telecom uses a profitability management solution to create income statements for each of its 21 million customers using ABM.  Data mining and statistical analysis on this data yielded hidden insights into the drivers of profitability.  Figure 4 shows an example of an income statement for a customer of a bank.  This income statement shows the gross contribution of the customer to profit (does not require ABC) and the net contribution to profit after deducting the ABC-derived cost-to-serve the customer.

Contribution Summary for a Bank Customer

For Year 2007

Figure 4: Customer income statement (line items in bold are from ABC).

Paradoxically, these new technologies offers fast results from ABC without the heavy lifting.  This is because cost rates from existing systems or analysts can be incorporated to support an initial view of profitability.  This allows quick results while creating a positive ROI that encourages later more in-depth analysis using ABM.  In some respects, this is “back to the future” where profitability management tools are first used to “see” the profit opportunities.  A deeper drill down using ABC may be postponed to a second follow-on phase when an organization desires to better manage and improve how they act based on the compelling figures surfaced during the first phase.

From a change perspective, this two phased approach helps improve commitment and the long-term success of ABC.  As changes are made to the business model, these new technologies allow faster more focused reporting of the impact.

Performance Measurement.  Performance management plays an important role in strategy execution.  It is used to measure goal accomplishment, provide feedback on performance, predict future performance, and trigger analysis and corrective action.  These benefits will only occur, however, if relevant and accurate performance measures are available for inclusion in performance management.

In organizations that integrate ABC with performance management, ABC is an important source of performance measures.  These measures are typically found in the process dimension of a scorecard where activity costs provide the focal point for target setting and scoring of goals around process performance.  In the case of a government agency, for example, as many as 25% of their performance measures were sourced from their ABC model.

ABC derived measures are also found in the customer dimensions of the scorecard where goals relating to customer profitability are set.  It would be difficult, if not impossible, to include these goals in the absence of an ABC model.  It helps communicate the insights of the profit cliff and drive action by a wider audience of responsible managers.

Financial Planning.  ABC supports the preparation of budgets and long-term plans that are logically derived from strategic goals and consistent with the relationship between goal achievement and resource intensity.  ABC models with predictive capability combine with forecasting and other analytic techniques to support fact-based scenario development.

In an insurance company example, ABC cost was used to optimize process performance.  Based on new levels of productivity, forecasting derived the volume of transactions for the process for the coming budget period.  Once the forecast was complete, the planner used ABC to predict the quantity of each type of resource required to handle the forecast volume of transactions.  The predicted resource costs were then incorporated into the budget.  This type of analytic support in budget preparation is a far cry from the “let’s add 10% to last year’s budget”.

Human Capital Management.  ABC today plays an important role in human capital management (HCM).  Many organizations, in both the government and commercial sectors, are working to be more efficient by using fewer people but at the same time struggling to keep internal knowledge and acquire the right level of skills.  It is difficult to predict the number of people that will be needed with certain skills and capabilities.  It is more difficult to justify the need for additional hiring in difficult economic times.

While solutions can pull all the information together and predict skills, capability and employee churn effects, ABC provides three important insights.  First, ABC analysis can be used to analyze high cost processes and improvement action taken to free up resources.  The freed capacity may be redeployed, using cross-training, to meet critical needs.  Second, ABC can be used to forecast the transaction level of activities, which are then used to forecast the amount of resources used to perform the new level of activities.  Finally, ABC input can be used to perform statistical forecasting to accurately determine the number of people required to support targeted products, channels, markets, customers, etc.

Many firms are beginning to use HCM solutions to bring all employee information into a single platform.  Analysis includes retirement planning, capacity planning, dissection of employee base using stratification and forecasting of areas of skills shortage.  ABC can be a useful complement to these systems by providing the necessary intelligence at the process level to drive such analysis.

Sustainability.  Many organizations today have goals to improve sustainability, reflecting market realities, pressures from stakeholders, and increasing government regulation in this area.  Improving sustainability requires measurement of carbon dioxide and other greenhouses gases, optimization of business decisions around profit and sustainability, compliance and transparency of reporting.  ABC can help in all of these areas.

For example, organizations are using ABC to measure, model and report the use of carbon dioxide alongside traditional costs and profitability.  An ABC carbon model can track sources of carbon (e.g., air travel) to the resources that consume the carbon.  The ABC model can track the amount of carbon used by each activity (similar to the consumption of resource cost in a cost-based ABC model), and flow carbon use from activities to the benefiting products, services and customers.  In this way, ABC facilitates the measurement, management and improvement of the use of carbon dioxide.  It helps suppliers communicate to their customers how much carbon is embedded in the products and services received, and, more importantly, it provides a quantification of the benefits to the customer of supplier programs to reduce their carbon footprint.

This latest iteration in the ABC Hype Cycle is where the full potential of ABC is finally realized.  Viewed correctly over 20 years ago as a tool of value, it has taken continuous development, learning and improvements in ABC software and enhancements in systems to solidify ABC’s place as a key ingredient of performance management.

CONCLUSION

Like most technologies, ABC’s life cycle is marked by changing attitudes and increasing diffusion into the marketplace over time.  Intense interest at the beginning of its life gave way to criticism and lowered visibility, followed by a longer, unpublicized period of steady growth in adoption rates and functionality.  It has now reached maturity and acceptance in the marketplace for management ideas and methods.

ABC evolved greatly over more than two decades.  Evolving from early experiments in costing, ABC emerged as a tool for profit improvement and was adapted for use in the extended value chain and multiple industries, and enhanced for resource and capacity planning.  In its most recent iteration, ABC is a multi-faceted algorithm and database of financial and organizational information.  It supports performance management systems where business users can access ABC-derived decision relevant information from their desk top.  These are the four generations of ABC.

Figure 6: The four generations of activity-based costing.

Understanding this journey provides important lessons as organizations continue to adopt and use ABC to create value.  One lesson is that ABC is an integrated family of analytic costing methods.  A single ABC model can support historical cost measurement, predictive cost measurement, resource planning, capacity planning, performance measurement and other analyses.

Another lesson is that the developments of ABC are sometimes misunderstood, and this may lead to confusion and rejection.  For example, assessing the value of ABC in lean accounting will result in one answer if the assessment focuses on the first generation ABC costing method.  It will result in a different answer if the focus is on ABC as a process-based resource and capacity planning tool.

As is true with any method or technology, ABC has gained impressive functionality over its life cycle (Figure 5).  ABC is at the heart of integrated performance management systems supporting measurement and analytic applications in multiple settings.  Concurrently, cumulative experience and new methods have lowered the cost of implementing and maintaining ABC systems.

Understanding the cost-effectiveness of today’s ABC is important to assessing its value as a strategic tool in today’s hyper competitive and volatile global economy.  Assessing yesterday’s ABC against today’s requirements is akin to assessing the power, comfort, handling, environmental impact, safety and fuel consumption of today’s automobile based on a study of the Model T Ford.  It is time to take another look at ABC.

About Cost Technology

Cost Technology designs and implements solutions to support fact-based decision making.  These solutions transform existing data into strategically meaningful and actionable insights in areas such as cost and profit management, financial forecasting, analytics, and performance management.  Since 1991, the firm has helped public and private sector organizations across the world improve performance by creating the knowledge needed to make every decision count.