For decades, Activity-Based Costing (ABC) has been an important tool for analysts and business leaders to assess their production and make course corrections necessary for survival and success. Today, there’s a much more detailed and accurate alternative — Quantum Costing — which calculates precise costs and profits at every level of detail. For many companies, this has been a game-changer.
To understand the advantages and benefits of Quantum Costing, let me provide some groundwork…
My Costing History
Fifteen years ago, I set out to create the kind of costing and profit analysis system I’d always dreamed of when guiding multiple companies. At first, I focused on Activity-Based Costing, as it was the only then-known methodology that came close to the objectives of indicating where money was being made or lost. My enthusiasm waned as I began reconciling variances between the projected and actual costs, and I started to see how much work was involved in refining the accuracy of the base cost increments needed for ABC.
I concluded that I’d need to create better cost breakdowns so the increments would be as precise as possible and I’d need a mechanism to make the results dynamic, so they could track changes in the company and in the market. If this could be automated, the workload could be reduced and the costing work repeatable across time. This led to the core mechanisms of Quantum Costing. (More on this in a moment.)
Unlike most costing practitioners, I and my team have spent more than a decade exclusively developing and systemizing a new multi-dimensional approach, working with hundreds of companies to integrate their wisdom while we dynamically model the internal and external drivers that are both predictive of (and actually control) company results. The result is much more accurate costing and profit analysis that reveals the interactions of cost drivers, and with a much-reduced workload.
The History & Weaknesses of Activity-Based Costing
Throughout history, every viable manufacturer has to have a working methodology to assess costs and set pricing. Analysts have long broken materials, labor and overhead costs into fixed and variable subsets, and done their best to connect these to production volumes so appropriate prices could be set and companies could remain viable.
In the late 1980s, computing horsepower was very expensive, so only the largest companies could implement the kind of detailed tracking needed for anything more than rudimentary production costing. At the time, ABC was popularized from the work of Dr. Robert Kaplan et al, as published in Harvard Business Review. It directly addressed manufacturers’ need for better costing and therefore facilitated better pricing and planning. The real innovation of ABC was to use manpower (which was being tracked for payroll purposes) as a surrogate for costs that are nowadays available as productivity and efficiency metrics. This is the most widely-used costing methodology and was pretty much the best-available mechanism until the invention of Quantum Costing in the late 2000s.
Lacking better alternatives, other industries have adopted ABC, even though the dynamics of their markets may vary significantly from those of manufacturing. Companies in distribution and service industries frequently borrow elements of ABC to assess various elements of their costs in situations where product costs are either well-known or not relevant to their business models.
The challenge for everyone is that ABC suffers from a number of inherent weaknesses:
- it requires substantial preparatory work in time studies and analysis;
- changes in processes and personnel require re-analysis;
- errors in incremental costs scale up to create large variances in actuals vs. projections;
- it fails to account for the dimensional considerations of business processes that are significant cost drivers;
- due to the high effort of preparatory analysis, reanalysis tend to be infrequent and so don’t track changes in market conditions or sales;
- and out-of-date factors drive erroneous conclusions, hurting company results.
Fixed and Variable Costs
Most ABC implementations utilize fixed and variable costs, which are well known, but frequently misused. The principal application for fixed/variable costing is to account for how costs are likely to scale when predicting the future. This is irrelevant when assessing costs that have already occurred — which are the very cost factors needed for ABC.
If you’ve ever been bogged down and unsure in analysis, this is the most likely area — how do you actually account differently for fixed and variable costs when calculating factors? And then how do you prevent fixed costs from scaling up with increased activity? For example, facility rent is not likely to change in relation to future production levels, yet every unit made or moved through the facility needs to carry its portion of the rent cost.
What we found is that few costs are truly fixed. For instance, lease costs are known, but will certainly change should the business scale up beyond the capacity of the facility or scale down below the financial limits of the current space. They’re also usually much smaller in absolute dollars than manpower or materials costs, which are both more significant and are also clearly variable. On the other hand, excepting significant variations in production, the unit cost of leases is unlikely to change enough to influence pricing and strategic decision-making. So, to best calculate the increments, fixed costs are treated the same as variable costs — that is, the cost amount is best divided into the production or activity being considered.
So, while the use of fixed costs is appropriate and necessary for rough projections and budget planning, it’s much less helpful in detailed cost analysis. I know this will be considered heretical by some, but the effort used to sift out and account for fixed costs is better spent on the usually-missed dimensional elements that really drive costs and cash-flow.
Multi-Dimensional Cost Factors
In the commonly-practiced use case for manufacturing, ABC typically considers materials, labor and overhead costs, and usually for the manufacturing process only. In the most sophisticated instances, granular costs for individual machine time or utilization of particular processes or departments across multi-level Bills of Materials may be considered. These implementations are highly dependent on the accuracy of sales projections and are most effective where production is closer to capacity and sales fluctuations are small. In the manufacturing case, activities can be good surrogates for scaling costs, and this has been the enabling concept of ABC.
Much more detailed costing can be highly beneficial, especially when applied broadly to the entire expense structure of the business. This is best done with a multi-dimensional approach where costs are tied to (and scaled by) the driving dynamics of the business. For example, the distribution industry knows precisely what the Cost of Goods is, but the costs of business scale along the dimensions of: supplier; assembly activities; product handling; transportation; customer type; and administrative support, amongst others. In health care, the common cost dimensions are: facilities; practice type; department; medication; supplies; payer; billing/collections; and overhead.
For accuracy, costs need to be attached to their dimensions and scaled appropriately within them. Delivery costs for a particular carrier need to be attached to deliveries made by that carrier, and scaled to the highest-possible level of granularity, be it: by the delivery; by the delivery mile; or by the delivery minute. Costs of marketing, selling, and monetizing (billing & collecting) various classes of customers need to be associated with those customer classes.
Cost assignment and scaling within operating dimensions and across the complete spectrum of expenditures produces highly accurate cost models. Much more importantly, the results of multi-dimensional costing surface previously-unseen interactions between dimensions, which can drive ground-breaking competitive insights for company leaders.
For instance, it may be possible customers that prefer a particular package delivery service tend to buy narrower product selections that drive smaller and less profitable order sizes. Or, customers that purchase odd order quantities don’t tend to purchase wide product selections. Or, a particular product line or items that utilize a particular process are underpriced, Or, perhaps, a particular customer group produces profit levels well above those of much larger accounts. All these examples can drive strategic direction.
How Quantum Costing Works
By the mid-2000s, the cost of computing capacity necessary to calculate very detailed costs began to come within range of mid-range companies, and cloud computing brought the price of high-end costing within the affordability envelope for practically everyone.
The “quantum” in Quantum Costing comes from the concept that costs are calculated at the smallest-possible increment of company activity, and this is the invoice line. Invoice lines are the perfect level of granularity because each represents a real-world quantity of a particular product sold to a real-world customer, and with specific dimensions like vendor, selling location, servicing location, sales rep, customer type, warehouse/direct, delivery method, etc.
Because of the multi-dimensional nature of Quantum Costing, this methodology reports not only the specific and detailed “hard cost”, but also quantifies inferences of other factors to influence costs of the particular item. For instance, product with a tendency to be ordered and shipped along with other items will tend to have a lower cost due to packaging and transportation costs being shared. Traditional analysis can’t show this, but it’s crucial to accurate cost assessment and insights that can drive market strategy and profit optimization.
Where ABC is primarily bottom-up, Quantum Costing is top-down, distributing known costs amongst the individual transactions that occur in operating the business. These individual costs may scale on either activities (like invoices, picks, units built, orders shipped) or production (revenue, COGS, gross profit, payroll dollars, etc.). Each cost is distributed either by the activity or pro-rata on the production measure, using more than a dozen different distribution methods. Using these mechanics, costs are distributed amongst the members of each related transaction pool.
In our implementation of quantum costing this is done dynamically, starting with estimates based on recent norms, later replaced by actual values as they become available. This results in much more accurate costing, and with system automation taking on the workload of distribution of costs, and maintaining up-to-the-moment values as business changes with normal progression and seasonality. It also accounts for shifts in sales and costs between locations and product lines.
The mathematical benefit is that cost increments always scale up to the actual values, and variances are nearly eliminated. The results support a very, very precise costing reconciliations. A by-product of the process is the near elimination of the overhead required for both the initial analysis and maintaining needed changes in cost increments across time. The system uses rules to automatically recompute and restate factors as the inputs change across years of operation.
Efficiency & Productivity Metrics (OCR & ROX)
Good, accurate, and detailed costing is vital for matching pricing to the real costs of delivering products and services to customers — at price levels that are both competitive and profitable.
This brings me to the core benefit for costing in the first place — operating efficiency. Ability to maximize product value moved per dollar spent determines profitability, cash-flow and market share for any company. This is the single, most-important element for the focus of executives, and the analysts that support them.
Efficiency metrics like OCR (OpCash Ratios) and ROX (Return on Expenses) are the critical metrics for understanding efficiency. They drive financial results like ROI, EBITDA and net profit — none of which can be directly controlled.
OCR is calculated by dividing OpCash (Gross Profit) by Expenses to find how much profit opportunity is produced by each dollar expended. For example, a company generating $5.6M in OpCash and spending $3.7M in operating expenses is creating $1.24 in profit opportunity for each dollar it’s spending on operations. This is the ceiling for profit opportunity that the company could theoretically see if expenses were zero. Increasing OCR can result in increased profits when expenses are controlled and is a valuable precursor to a company’s profit production.
The company’s actual profit production is reflected in the ROX measure, which is defined as realized profit per expense dollar. For example, $939K in profit produced by the same $3.7M expense total results in ROX of $0.254, or just over 25 cents of profit for each dollar expended. A penny increase in this number represents a whopping 4% increase in profit generation.
Where it begins to get interesting is when these metrics can be calculated at a more granular level so both profit opportunity and profit production can be compared between locations or departments, or can be assessed across time. Although still not directly controllable, they’re the result of productivity measures that most certainly can be controlled. So, a warehouse manager that’s working productivity measures like OpCash per manhour, or picks per week, or deliveries per day will be driving measurably higher OCR and ROX, and helping the CFO deliver increased EBITDA and ROI.
Multiple Cost Streams
To execute on very fine-detailed cost analysis, Quantum Costing recognizes that costs accrue to different elements of business operations. Cost drivers may be independently related to: suppliers; customer; sales reps or selling channel; operating units; product lines; transportation methods; or any organizational element of the company. Costs also scale differently for differing circumstances, varying by the unit quantity, delivery mile, geography, manhour, machine-minute, etc.
Quantum costing accounts for these factors, and provides for breakdown to the finest-possible level within these dimensions. For instance, delivery costs can vary between carriers and between delivery routes, so tracking and assessing costs at the greater level of detail delivers more insight into the cost and profit dynamics of the company’s activities.
The Magic of Correlations
The multi-dimensional nature of Quantum Costing produces a result that’s almost magical.
Subtleties in market and customer behavior become apparent, and can be exploited for substantial profit gains. You may discover the analysis quantifies the impact of unexpected correlations within your business processes or sales. For example, you may find that certain products with “normal” margins have lower handling costs and tend to be more profitable, or that customers in a certain demographic tend to buy a wider variety of items on an invoice, or that shipments in a particular segment cube out more efficiently for transportation. You’re almost certain to discover that your “second tier” accounts (usually much smaller than your top accounts) actually generate much more profit than the big ones. These insights can shift focus to more profitable areas, creating an edge that translates into higher profit and better market position.
The Haves and the Have-Nots
Typically, a leadership team that can post double-digit profit gains would be lauded as heroes by the company’s stakeholders. The insights of multi-dimensional cost analysis can, and do, give substantial competitive advantages to their practitioners, and produce profit rates that can be double or triple those of industry averages.
This is particularly true while the practice of detailed profit analytics is fairly new, with huge and unseen inefficiencies common in competitors and throughout most industries. Companies investing in detailed analytics are moving quickly to consolidate dominance in market and product areas where the highest profits exist.
In the distribution industry — a game of inches — the last decade has seen the emergence of analytically-driven players. The rapid adoption of advanced costing has brought the industry to a point where almost a quarter of companies are operating at profit rates above 15% — three to five times the typical rate, and well above the top rates of just ten years ago.
This is important because companies with advanced analytics are identifying and addressing issues invisible to those without. They’re also exploiting unseen opportunities inherent in highly-efficient customer relationships, and expanding their return by poaching accounts from competitors who don’t really know where the best opportunities lie.
Choosing the Best Methodology
Managing price points and upstream productivity measures increases operating efficiency which, in turn, are the drivers of company ROI, EBITDA, and profit rates. Increased performance in these ultimate financial measures is the follow-on result of precise and detailed costing, and the efficiency metrics like OCR and ROX that it supports. Focus on eliminating unnecessary costs, optimizing productivity, strategic pricing, and marketing strategy coalesce into profit and market-share gains.
Detailed and accurate costing is a vital function which can make or break a company and determine its market position. For now, choosing the better methodology can provide a real edge while competitors aren’t yet up to speed. Later, it will be a survival necessity when they are.
Shouldn’t your company be using the best-available methods?
To learn a lot more about Quantum Costing, LIPA, and advanced analytics you can get my book: Profit-Driven Analysis & Practices: The CEO’s Guide to Record Profits (ISBN: 979-8589295375). The book explains the field of LIPA (Line-Item Profit Analytics), and how you can use its unique metrics and strategies to outperform everyone else in cash-flow, profits, and market share. (Get it on Amazon at https://amzn.to/3tjr2VM) If you’d like to know more, you can reach me at 480-426-9955 or email rarias@waypointanalytics.com.
