Data Analysis of Capex Profitability Across the Full Life Cycle

Elena Smirnova, System Analysis Department St. Petersburg Information and Analytical Centre, St. Petersburg, Russia
ORCID: [0000–0002–4487–2594]

Abstract  The problem of investment projects efficiency assessment and commensurability of long-term effectiveness for the full payback period with increasing macroeconomic uncertainty remains relevant. The criteria used to make investment decisions at the planning stage do not always allow further financial results comparison for post-completion audit. In long term monitoring of capital expenditure profitability, we suggest to measure the absolute effect of project for the accounting date by the net interim value of accumulated cash flow. Based on this approach we also suggest using the average annual profitability index as a metric to assess the rate of investment profitability. And aggregated assessment of return on investment of the whole investment program can be made as weighted average profitability index.

Keywordscapital budgeting, net interim value, average profitability indeх, asset implementation, full life cycle costing

© The Authors, published by CULTURAL-EDUCATIONAL CENTER, LLC, 2020

This work is licensed under Attribution-NonCommercial 4.0 International

I. Introduction

Our research is focused on choosing key metrics for assessment of return on real investment. Additive criteria of absolute and relative return are needed for individual projects, as well as summary data for all projects being part of the company’s investment program that are measurable for the accounting date.

Real investment programs of major holdings have tens or even hundreds of projects aimed at creating new production facilities or acquiring capital assets, varying in technologies, scale of investment and implementation timeline. The main methodological problem of summary assessment of streaming data describing the state of the investment program for the current date is the heterogeneousness of projects, with different project start times and terms of implementation of assets, as well as with various investment values.

Analysis of investment efficiency across the full life cycle of the “project→asset” system requires a dynamic assessment of the actual return level at the implementation stage after the actual breakeven point. From the point of view of long-term expenditure management, both control over budget for the investment project until the production launch and regular economic monitoring of the current dynamics of the financial result and the actual rate of return are needed.

Results of investment projects implementation and their financial return often differ from those initially planned, and investors’ expectations on their profitability are not fully met. Limited controllability of investment results, both due to immature processes of corporate strategic management and unpredictable changes of environmental attributes, is a key challenge for the financial management that hinders the implementation of company’s strategic goals.

We suggest criteria for assessing current investment efficiency in absolute and relative measurement which can be used for practical organization of economic monitoring of both individual projects and the company’s whole investment program across the full life cycle, including the implementation stage. That said, the assessment of achieved financial results of the project and profitability levels is carried out over a partial period, only based on the known actual data — from the beginning of project implementation to the current monitoring date, without using the forecast of further financial return over the full planned life of the asset implementation.

Information and analytical component of investment profitability monitoring is aimed at increasing the quality of business management at the strategic development horizon, as well as the company’s economic value.

II. Literature Review

A. Uncertainty of the Future

Monitoring of investment efficiency is a regular process of collecting, structuring and consolidating information, analysis of the system’s changes over time [1]. Such monitoring on capex profitability parameters is aimed at dynamic assessment of actual return resulting from the investment project. For example, according to the PwC’s ‘We need to talk about capex’ telecom industry report [2], more than half the respondents in our survey estimate that about 20% of their company’s capex is spent on assets which don’t recover their cost of capital.

PwC interviewed 22 telecoms executives from a representative cross-­section of companies and regions to get a better picture of what lies behind the industry’s. Their comments suggest that there are four key reasons for the inefficient allocation of capital: capex planning driven by technology, not business objectives; investment decision structures lack sufficient accountability and incentives; new projects do not benefit from lessons learned; capex proposals have too much paperwork and not enough insight.

The Russian experience of analyzing the causes for underachievement compared to initially expected results during implementation of well-planned investments is presented by Alt-­Invest [3]. Four groups of factors were identified that lead to low average results compared to those forecasted in the business plan: excessively optimistic forecast as a marketing ploy, adjusted to investor’s skepticism; overvalued product attractiveness for customers; omission of substantial expenditures and underestimation of organizational and technical problems; reverse influence of the implemented successful project on the environment: release of a new product changes competitors’ tactics, customer preferences and suppliers’ price policies.

B. Commonly Used Criteria

In accordance with the existing theory of financial management, to achieve the goal of maximum value, companies maximize the net present value of their investments.

Capital budgeting is a tool that can be used for very simple operational decisions such as equipment replacement or more complex strategies such as the construction of a new plant [4]. When considering the importance of capital investment decisions, it is imperative that managers use the appropriate practice to ensure a sound decision [5]. More sophisticated capital budgeting practices are discounted cash flow (DFC) that take into account the value of money over time [6–7]. Almost all financial managers use the following set of efficiency criteria to assess investment projects: net present value (NPV), internal rate of return (IRR), profitability index (PI), payback period (PP), discounted payback period (DPP).

The interest in understanding the capital budgeting practices used by companies in planning was first observed in the 1960s. Evidence from the 60s and 70s reflected a certain trend to gradually use models that were theoretically superior based on DCF [8]. The fields of engineering economics and corporate finance have long stories of research on how to evaluate profitability choosing an interest rate for an investment project [9].

One of the first researchers to discuss the practical aspects of choosing investment project efficiency indicators was Pike [10]. Then this topic was further developed by a number of authors who presented the results of surveys carried out among chief financial officers in different countries: “How do CFOs make capital budgeting and capital structure decisions?” [11],”Comparative financial practice in the US and Canada: capital budgeting and risk assessment techniques” [12], “Cost of capital estimation and capital budgeting practice in Australia” [13], “Low-intensity RandD and capital budgeting decisions in IT firms” [14], “The capital budgeting evaluation practices of building contractors in Hong Kong” [15] “Capital budgeting practices: a comparative study of the Netherlands and China” [16].

Empirical research provided inconclusive evidence regarding the capital budgeting practices among practitioners; while several researches showed the payback period (PP) as the most popular technique employed in evaluating projects, other investigations demonstrated that discounted cash-flows practices are the most frequently used capital budgeting techniques [17–18]. Assessing the capital budgeting proposals is part of the decision to make investments [19]. Within that context, the financial management and the capital investment decision-­making are fundamental for the survival and success of the company in the long term [20].

C. How to Measure Actual Profitability

Managers consider the financial analysis and cash flow estimation stages to be the most difficult in the investment project appraisal process, because they have difficulty analyzing which projects are likely to be the most or least profitable. Сlassic criteria for making investment decisions at the project planning stage later prove inapplicable for monitoring the actual performance of the asset during its full lifecycle.

Table 1. Profitability Monitoring Criteria

Stage of full life cycleRelevant criteria
of project
Project schedule varianceEarned valueTechnical Preparedness Factor
of asset — 1st phase (NPV < 0)
Net accumulated discounted cash flow Anticipated breakeven point (payback period)
of asset — 2nd phase (NPV > 0)
Net accumulated discounted cash flow Profitability indexProjected full payback periodLife expectancy

The full life cycle of the project → asset system begins at the moment of forming an investment idea and ends with achieving the expected positive financial result that corresponds to the planned capex profitability due to the revenues from the real asset implementation.

The period of monitoring of investments coincides with the full life cycle and consists of three consequent stages: pre-investment, investment and then new asset implementation. Economic analysis of capex efficiency suggests that the asset implementation stage is divided into two phases: before and after the accumulated cash flow reaches the investment breakeven point (Tab.1).

Relative assessment of return on investment is only possible on the second stage of the creared asset implementation when the investment profitability index becomes positive. The second stage is characterized by the highest uncertainty both in terms of the duration of useful life of the asset and the extent of changeability and variability of the expected cash flow elements that define profitability indicators.

The possibility of such a clear delineation of the implementation stage into these two phases, without NPV going back to negative, is equivalent to the requirement that the internal rate of return has the unique value. The necessary condition for this is known as Norstrøm’s ‘sign rule’ [21] formulated with the number of sign reversals in the elements of net accumulated discounted cash flow: if the last element of a chronological array has nonzero value and the sign reversal (from ‘–’ to ‘+’) happens only once, then there is only one positive IRR value.

Properties of IRR as a polynomial root restrict its use as a profitability indicator [22]. In fact, there are many ‘non-conventional’ [23–24] projects, for example, large investment projects with several stages that require additional investments in the middle of implementation. Also a wide discussion aroused a series of articles by Magni on iterative measuring of the investment project average internal rate of return (AIRR) [25–28].

IRR analysis of such investments is difficult from the mathematical point of view, while from the monitoring point of view, the analytical assessment of the relative efficiency level (per capex unit) can be carried out.

The economic assessment of cash flow in financial analysis uses NPV (net accumulated discounted cash flow) that is evaluated on a total basis of cash inflow-­outflow for the project that are recalculated with the discount coefficient against the initial investment date. The moment when NPV becomes zero, when the accumulated discounted sum compensates investment expenditure, is the investment breakeven point.

When choosing projects, businesses usually focus on the planned positive NPV, i. e. nonzero financial return. This makes the second phase of the implementation stage, when target requirements for project efficiency can be related to its actual returns, the most interesting for economic monitoring of investments and setting up a cost data base.

In order to provision the database of the cost engineering, an average annual profitability indicator is needed [29] for the accounting date that projects can be compared against, as well as aggregated in company’s investment portfolio [30].

Investment project feasibility study and assessment of its expected profitability are carried out in accordance with the project financial model based on calculation of net accumulated discounted cash flow (~NPV) that is the summary evaluation based on bringing cash flow elements of future periods back to the past — to the moment of initial investment.

With profitability monitoring we can see that the actual NPV is gradually accumulated over the incomplete period (m years) assessed as a partial sum of the first m elements of NPVm based on the known actual data:


where m is number of the interim accounting period;
I0 — sum of initial project investments (negative); CFi — cash flow over i period; r — rate of discount; PVm — accumulated discounted cash flow (present value) as of mNPVm — net accumulated discounted cash flow (part of NPV) as of m.

The full payback period of an investment project refers to the time needed for NPVm to become positive, proportional to the planned one with acceptable accuracy.

III. Results

The primary process in monitoring is the observation of actual values of cash flow elements and their comparison to the planned ones. Then it requires a dynamic reassessment of investment project indicators both by the moment it started and the current moment. For adjusting last years’ data to the monitoring accounting date, we will use compounding according to the terminal value formula. We are defining two new indicators: NIVm and АPIm.

Net interim value NIVm is an contemporary assessment equivalent to NIVm as of the monitoring date m and commeasurable with the CFm for the financial year m, that is included as the last term of the sum without an adjustment multiplier. Due to its economic sense, this criterion most accurately corresponds to the analysis of current return on investment and focuses on relevant data of profitability monitoring in the price scale of the financial year. CFm can be used for building motivation for financial managers responsible for this project.

Net interim value (NIVm) of the project cash flow as of the accounting date m is the future (terminal) value of NPVm partial sum with r discount rate (confirmed as a discount rate for the financial model of this project):


where TIm is terminal investments as of m


and IVm is interim value as of m


For monitoring, absolute effects of investment project implementation for the current date are measured by: cash flow CFm over financial year m, interim value of project cash flow over the period of project implementation IVm, as well as its net interim value NIVm. These partial terminal assessments of financial results refer to the same moment, and, in this sense, they are additive — they allow direct interproject aggregation of values for measuring current financial return on the program in general.

Ratio of investments of different scale against their return requires the use of a relative value. This can be either investment profitability index (growth index):


or the current share of discounted value in initiat investment amount (increment index).

Time rationing of the last value provides “the indicator of the speed of specific increment in value” (IS) suggested and justified by A. Kogan [31–32] as a relative criterion for accurate correlation of efficiency levels of heterogeneous projects that differ both in scale and timelines, where n is the full term of project:


This metric is a dynamic, relative and average annual indicator that can be used for measuring the current profitability level for a partial period — after first m income periods of implementation of the asset created as a result of the investment project. And average profitability index (API) has the same properties


For introducing profitability monitoring, as an investment efficiency criterion we suggest using the interim average profitability index АPIm that is defined as the average annual ratio of the result PVm to investment amount I0 as of the accounting date m:


Transition from the discounted value to interim value has no impact on the calculation of the profitability index — this indicator is invariant with respect to the choice of the way of bringing the cost indicators to the accounting date, since


So АPIm calculation can be made with interim value IVm:


Terminal investments TIm can be used as scales for measuring average weighted profitability of the project flow within the whole investment program (total average profitability index).

Summary aggregated assessment of return on investment of the whole investment program consisting of a number of heterogeneous projects can be based on APIm[k] individual indicators as weighted average profitability index WAPIm as of accounting date m:


where k is investment project number; Q — number of monitored projects; APIm[k] — current average profitability index of the k’th project; and TIm[k] — terminal investments of the k’th project.

The suggested approach makes it possible to use three key metrics for assess the actual project profitability:

• Interim (compounded for the m monitoring date) value of certain projects that allows their correlation in ‘plan’ and ‘actual’ dimensions and aggregation of the financial result for the date for the investment program as a whole.

• Current average profitability index АPIm is a relative metric of return on investment level.

• Weighted average profitability index (WAPIm) as of current date where terminal investments are used in the denominator as scales.

We suggested using a new indicator and a corresponding term, interim value, for contemporary assessment of cash flow and we are open to discuss this approach and alternative terms. The assessment of an project’s achieved financial results and expenditure profitability level is conducted for an incomplete period, only at the horizon of known factual data, from the beginning of project realization until the current monitoring date, without using the forecast of subsequent financial efficiency for the complete planned period of the investment project.

IV. Discussion

The proposed analytical metrics are additive and can be delineated by the dimensions of the cost database that serves as a source for automated cost engineering systems. The cost database of investment history in per project breakdown serves as a knowledge source for cost engineering across the full life cycle. Additive metrics of investment profitability use allows to apply modern information technologies for multidimencional analytical processing of data structured as a hypercubes (OLAP).

The starting point for the analytical system based on profitability monitoring data is the information survey of company’s investment activities, including:

• making a catalogue of monitored projects;

• justifying the initial information on cash inflows and outflows;

• choosing assessment criteria to be included in the analytical report;

• identifying information sources and departments in charge.

The monitoring system project is executed by an economic service that coordinates informational interaction between different departments and carries out analytical data processing.

Among other participants of the monitoring system are relevant services: technical and commercial services that measure actual values of the key parameters that they earlier used to justify the draft project. Investment committee is the recipient of monitoring’s accounting and analytical information.

Taking into account annual cycles and seasonality of investment management processes, we recommend to update monitoring data quarterly and prepare an annual summary analytical report. The costs of monitoring process are offset by the systematization of risk management expertise across the full life cycle of assets created as a result of investment.

Automated monitoring requires a consolidated register of investment results. Fields of database records for each project need to have attributes both for storing initial information and for analytical indicators of grouping (managerial classifiers), showing similarity of projects (industry, technology, region, profitability).

In order to generate regular statements on monitoring data, markers for project breakdown based on key profitability indicators are incorporated in the register structure:

• plan-actual deviation analysis: project is working better/worse than planned

1st group — profitability better than planned;

2nd group — profitability worse than planned;

3rd group — project inefficiency have been revealed.

• breaking even (if the investment breakeven point has been passed)

project subgroup with ‘–’ marker — NIVm < 0;

project subgroup with ‘+’ marker — NIVm > 0.

Table 2. Groups on Profitability

Group of projectsNumber
of projects
1st groupincluding ‘+’ subgroup
2nd groupincluding ‘+’subgroup
3rd group
All projects

The efficiency criterion for investment project grouping can be both absolute (NIVm) and relative (APIm). In the second case, the analysis makes sense only after breaking even (group ‘+’). A suggested template of an analytical report structure based on investment profitability monitoring data is shown in Table 2.

The analytical assessment of the actual full investment payback period can be based on economic monitoring data referring to anticipated scenarios and models of development of risk factors. The analysis of impact and forecast of development of substantial factors that cause unfavourable deviations in efficiency levels provides an opportunity to adaptively manage investment profitability, including adjustment of the approved plan and assessment of options for wrapping up the project that does not pay back or removing an asset with a negative ownership cost from operation.

Regular profitability monitoring of investments forms an informational and analytical foundation for planning new projects while taking into account technological, market and financial experience of previously implemented projects: statistics of deviations, profitability level, trends of external risk factors development, acceptable adjustment solutions, and recommended real options.

Under the new economic conditions, the problem of accurate planning of the full payback period given the dynamics of actual economic efficiency of implemented investments at the stage of implementation of the asset is becoming increasingly relevant. The alternative to the expert intuition can be scenario modeling based on big data and options analysis, but the growing macroeconomic uncertainty does not always allow to describe even the structure of the multitude of anticipated events.

V. Conclusion

The proposed criteria for assessment of contemporary capital expenditure efficiency in absolute or relative terms may be used for practical organization of profitability monitoring of both individual projects and a company’s whole investment program across the full life cycle of the projects. Using such an approach, we can practically compare heterogeneous — in amounts and terms — investment projects as parts of a long-term program, and it can serve as a methodical basis for monitoring of investment profitability across the full life cycle of “project→asset” system.

The consolidated average annual index of capex profitability provides an aggregated estimate of the summary level of investment program profitability for the monitoring date. Accumulation of investment monitoring data shapes an information and statistics base that can be used to justify new projects involving previous technological, market and financial expertise: deviation statistics, level of actual effectiveness, models of external risk factors and feasible set of corrective managerial actions.

The digital transformation of business opens up an opportunity for regular analytical processing of the information collected in a corporate data base for obtaining useful knowledge and making strategic decisions. The focus shifts to dynamic reassessment of previously adopted investment projects for measuring long-term effectiveness and economic efficiency at the stage of implementation of assets that capital was invested into.

Updating parameters of an investment project during implementation of business assets turns the financial model into its digital twin that provides feedback and produces helpful managerial information.


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