Cost Benefit Analysis

Forecasting and CBA

Option 1

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As we are discovering, Cost Benefit Analysis is based on assumptions about financial forecasts of future cash flows and expenses. Since the future is unknown, getting consensus on inputs can often be the most challenging part of running a Cost Benefit Analysis.

In Assignment 2, we find five colleagues who each have very different views of the future. Referencing our readings this week and drawing on your own personal experiences, answer the following questions:

  • Why do skilled professionals working in the same business often have significantly different forecasts and views of the future? Share an example from your own work experience where your colleagues had very different forecasts for the same item.
  • How can we make better use of data (past performance, industry outlook, etc.) to improve our forecasts and resolve disagreements?
  • Would “sensitivity analysis” have helped Management understand the potential variations driven by changes in assumptions?
  • After the forecast is complete, describe the communication process you would use to convey results and successes to stakeholders, lenders, and employees.

– OR –

Option 2

As you’re learning in Assignment 2, a key technique in managerial accounting/finance is the use of “Cost Benefit Analysis” to help management make better business decisions.

  • Define this approach in your own words and discuss 2 applications of this concept in your current work environment (examples might include make vs. buy, plant location, new product or packaging, downsizing, acquisition/divestiture, etc.).
  • Discuss a variable or assumption within the project where the data was difficult to obtain — and what you did to develop a reasonable assumption for the project economics.
  • Additionally, share or create one example where using financial data and cost benefit analysis that did, or could have, led to a better decision.

peer#1

VALENTINE ANEKE

RE: Week 9 Discussion

COLLAPSE

Dear Class,

Based on my experience, I’ll choose option 1.

Within our future budget cycle, the sales teams always come up with their numbers/targets for the upcoming year. This has always been the case, each sales inputs their target projects or market and are consolidated by the regional sales manager for budgeting. We had many cases of sales managers over-promised and failed their budget, in that case as a multinational, these numbers are reported to the group. Within this exercise, shareholders’ anticipation is high. The natural evolution once the sales team states their budget, the group appropriates funding for their task which includes manpower, raw materials, service contracts, utility, increased rent spaces etc. all in view of a successful year.

  • Why do skilled professionals working in the same business often have significantly different forecasts and views of the future? Share an example from your own work experience where your colleagues had very different forecasts for the same item.

This achieved though either selfish approach or working in Silos. Every individual first fuel of knowledge comes from within, simply saying it’s natural, based on their past experience or individual opinion to be self-centered. I had 4 Regional sales managers who always tried to offer a can’t miss budget (1), and underperformed due to either economical or unforeseen circumstances. This approach changed, as they failed to understand the collective nature and strategy of the company. I recall in 2016, we changed this approach, and budgeting was achieved with all department’s input. The cards were on the table, each department now understood how their choice affected the global organization. The elephant in the room was eliminated, the selfish barrier based on either target bonuses or tainting another colleague was done.

  • How can we make better use of data (past performance, industry outlook, etc.) to improve our forecasts and resolve disagreements?

The best way to convince anyone is to depict the situation graphically and prove through some methods. I strongly feel clarity, roadmap, empowerment and communication is key. (2). Our model changed to more Quantitative approach, with predictive and prescriptive analytics based on our outcome. when it came to budgeting, we used various tools within the cycle;

      1. Descriptive: Gathering as much past data, viewing the behavior (Trend Analysis), and based on that information, moved to define which predictive method will define our best outcome. (3)
      2. Predictive: Predicting based on standard deviation, then moving average and further smoothing to reduce error. Regression demands analysis on past customers etc.
      3. Prescriptive: Based on quantitative data, give graphical representation to all stakeholders for the best decision. i.e. Decision tree.

This model of budgeting has tremendously improved our exercise, and the strategy to achieve those outcomes have been further simplified with great operational plans.

  • Would “sensitivity analysis” have helped Management understand the potential variations are driven by changes in assumptions?

Indeed this helped as its all part of our model, with this being a tool, management gets to understand the impact of their choices or postmortem of What-if based decision. Here, we get to see the future at a glimpse and plan if the situation is retracting from the strategy.

  • After the forecast is complete, describe the communication process you would use to convey results and successes to stakeholders, lenders, and employees.

In my view the buy-in starts from convincing each stakeholder of the budget process, within that same frame, we agree on the intended outcome for the good of the group. This will be communicated through the exercises from the aligning the strategy with operational plan.

References:

      1. JWMI, Wk9 Video- Forecasting
      2. Finance for nonfinancial managers, Siciliano, 2015. pg161
      3. http://www.statisticalforecasting.com/forecasting-methods.php

peer #2

Ewelike Alaekwe

RE: Week 9 Discussion

COLLAPSE

Hi Everyone,

I could barely believe it is September already!

What is Cost-Benefit Analysis and Why is it important in business planning and forecasting? My DQ post this week will try to answer this question and connect it with the current pandemic situation in the world.

Luke 14:28 says: “For which one of you, when he or she wants to build a tower, does not, first of all, sit down and count the cost and see if he or she has enough capital to complete it” (1). This is the first part of cost-benefit analysis – counting the cost.

In my words, Cost-Benefit Analysis (CBA) is a tool business managers use to count the cost of an investment, count the benefits the investment will yield and compare the cost and benefits to see if it is worth undertaking the investment. More so, CBA can be expanded to include risk analysis – so in this case, the manager considers if the benefits of the investment are worth not just the apparent financial costs but also the risks involved in the investment. The investment risks can be quantified in dollar terms and incorporated in the cost estimates or reflected in the discount rate.

This year 2020 will not be forgotten easily, and it is definitely a year I would say that no business plan and forecast envisaged. I know most corporate organisation do have business continuity plans, crisis management plans and emergency response plan. I am almost certain that none of those plans or any SWOT analysis envisaged a world as we have seen in 2020, especially in Q2. I guess companies going forward will add pandemic to their business opportunities and threats going forward when doing a SWOT analysis – remember that the pandemic is both an opportunity and a threat depending in which business sector you operate (2).

However, I strongly do believe that the companies that reacted fast and efficiently to the pandemic are the ones who had a plan of some sort from which they would adapt and make necessary changes to navigate the current realities. So, COVID-19 pandemic is a classic example of the importance of business planning and forecasting.

For instance, my company had a base case financial plan that budgeted $18bn in capital expenditures and about $1.5bn in stock buybacks based on oil price at $60 per barrel. However, when the pandemic struck, oil price crashed so badly that oil price future was negative at some point, and we had to adjust our plan to reflect current realities (3, 4).

As you will see in the reference number 3, one of the things we did was to cut our CAPEX budget for 2020 by about 20% (~$3B). How did we know which CAPEX budget to cut? All our capital projects are ranked based on CBA and to make a budget cut, we reviewed all projects CBA’s to reflect the current economic realities and re-rank the projects. With the new ranking, we select the projects that are resilient financially, aligns with our long-term strategy and fits into our current budgets. It comes as no surprise that most of the budget cut (about 83%, $2.5B) went to the oil exploration and production division – my affiliate’s project for next was cut.

At my level in the organisation, I am currently working on a preliminary study for an oil field development and we use CBA to choose between two or more technologies. To share a specific example, I designed an oil producer well but the Reservoir Engineer wanted to incorporate an Intelligent Well Completion (IWC) in the design because it gives more flexibility in managing the oil and water production from well – it helps us delay and reduce water production (what we call water breakthrough). The Project Manager, whom we call Petroleum Architect, asked me what will be the cost impact on the well cost (DRILLEX) and what are the operational risks with using the IWC technology. To the Reservoir Engineer, the Petroleum Architect asked what are the benefits in dollar terms of using the IWC technology.

I worked with the Reservoir Engineer to build a CBA for the IWC technology – he worked on forecasting the incremental benefits while I worked on forecasting the incremental cost. However, we also added a second option of using an older, cheaper but not so intelligent technology – manual sleeves. We used a nominal payback period to analyse both technologies against the option of not implementing anyone at all.

Forecasting the upfront costs associated with each technology was easy – we historical cost of the technology from previous projects both in our affiliate and in other affiliates. More so, we have vendors who are more than willing to provide us with a free current cost quotation. However, estimating the benefit is not easy – it is based on the assumption of how much extra barrel of oil we can produce by implementing the technology that helps to delay and reduce water production and also on the ever-volatile oil price. There are historical data from previous projects, but there is so much variation from one well to another and from one project to another – making so difficult to use these data for this particular well. Another variable that was hard to forecast is the Mean Time Between Failure and the cost of failure of the technology during the productive life of the well. In some projects, there have been no failures while in some others there have been significant failures.

To proceed, we created three CBA’s – worst case, most-likely and best case – the major difference for each case is the forecast for the amount of extra barrels of oil we can produce for using each technology (5). We then performed a sensitivity analysis for each cased using two independent variables – oil price and each technology MTBF (6).

By using multiple scenarios CBA and sensitivity analysis, we were able to present to the Petroleum Architect the range of possibilities for implementing either the IWC or Manual Sleeve technology as it compares to doing neither of them. The Petroleum Architect was able to use the result of our analysis to convince our management to approve the implementation of the IWC technology even though it would mean an initial upfront incremental cost of $7M per well. Hopefully, we have made the best decision – only time (3-5 years) will tell!

Thanks for taking the time to read my verbose post – your feedback is welcome.

References

  1. https://www.biblegateway.com/verse/en/Luke%2014:28
  2. Siciliano, Gene. Finance for Nonfinancial Managers, Second Edition (Briefcase Books Series) (p. 165). McGraw-Hill Education. Kindle Edition.
  3. https://www.cnbc.com/2020/06/16/how-negative-oil-prices-revealed-the-dangers-of-futures-trading.html
  4. https://www.total.com/sites/g/files/nytnzq111/files/atoms/files/march-2020-action-plan-at-30-dollars-per-baril.pdf
  5. Managers Toolkit. 2006. Net Present Value and Internal Rate of Return: Accounting for Time. Havard Business School Press.
  6. https://corporatefinanceinstitute.com/resources/knowledge/modeling/what-is-sensitivity-analysis/

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