Tips and Tricks for Optimising Excel

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Tips and Tricks for Optimising and Using Excel - avoid common problems with spreadsheets and analysis

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  • 1. www.hanrickcurran.com.au Optimising Excel Using Excel to optimise decision making and avoiding common problems with spreadsheets and financial analysis June 2014

2. 2experience. new thinking Todays presenters 3. 3experience. new thinking Todays agenda Learnings from implementing FAST at Wilmar with Gerard Cooney Common problems seen in practice with Matthew Green Spreadsheet Detective and its review abilities with Anthony Berglas 4. 4experience. new thinkingexperience. new thinking 4 Insights from implementing the FAST standard at Wilmar Sugar Gerard Cooney Implementing FAST 5. 5experience. new thinkingexperience. new thinking 5 A review of the implementation of the FAST modelling standard at Wilmar Sugar Gerard Cooney (fomerly Sucrogen and CSR Sugar) Implementing FAST 6. 6experience. new thinking The Problem Excel is ubiquitous in business User friendly Very flexible These attractive attributes cause problems: Everyone thinks they can use excel effectively Models structured using the idiosyncrasies of the user The result is often a mess 7. 7experience. new thinking Key Problems Every model is structured differently Difficult to review and audit Prone to errors Difficult to modify Difficult to understand 8. 8experience. new thinking 1.4 metre long formula =IF(AND($N971,$O971),$F97*$I97*IF(AND(HeavyVehInd=2,X $4>=RoadStartYr),(1-$L97),(1-$K97))*(1-INDEX (X$5:X$7,MATCH($Q97,$Q$5:$Q$7,0))), IF(AND($N97=1,$O97=1),IF(OR(BiomassInd=1,AgInd=1),0,IF(X$4> =MAX(BiomassStartYr,AgStartYr), $F97*$I97*IF(AND(HeavyVehInd=2,X$4>=RoadStartYr), (1-$L97),(1-$K97))*(1- INDEX(X$5:X$7,MATCH($Q97,$Q$5:$Q$7,0))),0)), IF($N97=1,IF(BiomassInd=1,0,IF(X$4>=BiomassStartYr,$F97*$I97*I F(AND(HeavyVehInd=2,X$4>=RoadStartYr),(1-$L97),(1-$K97))*(1- INDEX(X$5:X$7, MATCH($Q97,$Q$5:$Q$7,0))),0)),IF($O97=1,IF(AgInd=1,0,IF(X$4> =AgStartYr,$F97*$I97*IF(AND(HeavyVehInd=2,X$4>=RoadStartYr),( 1-$L97),(1-$K97))*(1- INDEX(X$5:X$7,MATCH($Q97,$Q$5:$Q$7,0))),0)))))) 9. 9experience. new thinking THE FAST STANDARD What does it stand for? Flexible Accurate Structured Transparent http://www.fast- standard.org/ 10. 10experience. new thinking FLEXIBLE Design and modelling techniques must allow models to be both flexible in the immediate term and adaptable in the longer term. Flexibility is born of simplicity. 11. 11experience. new thinking APPROPRIATE/ACCURATE Models must reflect key business assumptions directly and faithfully without being over-built or cluttered with unnecessary detail. 12. 12experience. new thinking STRUCTURED Rigorous consistency in model layout and organization is essential to retain a models logical integrity over time, particularly as a models author may change. 13. 13experience. new thinking TRANSPARENT Simple, clear formulas that can be understood by other modellers and non- modellers alike. Confidence in a financial models integrity can only be assured with clarity of logic structure and layout. 14. 14experience. new thinking Key Attributes of FAST model Use of calculation blocks where the calculation ingredients are shown explicitly and appear directly above the calculation Calculation ingredients link directly to the source (either input data or precedent calculation block). There is no daisy changing of links. Link labels and units as well as numbers, and enter only once Use of timing flags Also: Use of short formulae Constants only entered once. Parameters only calculated once. Consistent formulae across a row. Consistent use of columns within a sheet All inputs are collected on input-only sheets and colour coded to show explicitly Formatting consistency Diligent use of units Separate calculation engine from presentation output. 15. 15experience. new thinking Key Attributes of FAST model Use of calculation blocks where the calculation ingredients are shown explicitly and appear directly above the calculation Calculation ingredients link directly to the source (either input data or precedent calculation block). There is no daisy changing of links. Link labels and units as well as numbers, and enter only once Use of timing flags 16. 16experience. new thinking Secondary Attributes of FAST model Use of short formulae Constants only entered once. Parameters only calculated once. Consistent formulae across a row. Consistent use of columns within a sheet All inputs are collected on input-only sheets and colour coded to show explicitly Formatting consistency Diligent use of units Separate calculation engine from presentation output. 17. 17experience. new thinking Excel example REVENUE USING A TYPICAL APPROACH Sugar Revenue 5,870 $ Molasses Revenue 120 $ Total Revenue 5,990 $ 18. 18experience. new thinking Common Complaints Doesnt a standard approach stifle creativity It takes too long to model using the FAST Standard 19. 19experience. new thinking Resources http://www.fast-standard.org/ http://info.f1f9.com/31-day-financial-modelling- course http://www.fi-mech.com/ http://www.financialmodellinghandbook.com/ 20. 20experience. new thinkingexperience. new thinking 20 Understanding the common issues we see with Excel spreadsheets, some conceptual insight into how errors occur and some suggestions on how to prevent them Matthew Green Common issues with Excel spreadsheets and models 21. 21experience. new thinking My agenda How prevalent is Excel Common problems Error research The need for graphical presentation of data 7 steps to review your spreadsheets Practical learning's and takeaways 22. 22experience. new thinking Typical balance sheet Excel used in the following key areas and calculations: Account reconciliations Other asset listings and amortisation Fixed asset registers and depreciation Deferred and current tax Intangible asset reconciliations Impairment models Debt covenants Interest accruals Employee benefits Derivative reconciliations and to cross check bank valuations Spreadsheets for transactional reports with Pivot tables for further analysis Consolidation schedules 23. 23experience. new thinkingexperience. new thinking 23 "I suppose it is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail." Abraham Maslow, 1966 24. 24experience. new thinking Excel & Accountants like giving your kid a chainsaw, powerful tool, but does he really understand what hes got in his hands and how to use it? You have to ask yourself: Is this going to end well? (And No, hes not getting one for Christmas!) 25. 25experience. new thinking How many problems really exist? In our experience, most spreadsheets are poorly developed. This is probably because there isnt much formal training on how to build a spreadsheet and people dont have time to build them so that they are optimised for their purpose and to support decision making. Want to see some examples? 26. 26experience. new thinking Common problems Confusing, complicated formula Unstructured layout Formula & Function errors Range & Pointing errors Hard coding Remote references Empty precedents 27. 27experience. new thinking Confusing and complicated formula A real life discussion thread in an Excel specialist LinkedIn group. Why would anyone want to nest more than 1 If statement, let alone 8? Can you imaging how hard it would be to unravel an error in these If statements? 28. 28experience. new thinking Inconsistent build Sundry income inconsistently treated in six operating sites in budget file taken from board papers. In some sites, sundry income was included in total revenue and gross profit. In other sites, sundry income is excluded from both, but is factored into net profit. Site analysis based on GP would favour those with the sundry income in their GP. This error would not have been apparent to directors in their decision making. Source: corporate transaction, target budget file 29. 29experience. new thinking Inconsistent build Budget model for 6 operating sites in board papers. Site A calculated direct wages % based on net metered win. Site B calculated direct wages % based on gross profit. Not a big difference, but makes comparison across sites difficult. Why is there a business reason for the two sites to have different basis of calculation Site A Site B Source: corporate transaction, target budget file 30. 30experience. new thinking Hard coding and format Common example of a quickly built spreadsheet. Note the hard coded information buried in formula, in this case the CPI increase rate for the leases. Note the inconsistent number formatting, doesnt help the reader with assessing information. Whilst the outcome is quantitatively accurate, the poor design makes in hard to review and leaves the worksheet prone to error. Lease commitments: No later than 1 year Office premises to 14 October 2018 annual rent 100000 Monthly Rent to 31 October 14 8333.333 83333.3333 annual rent after 1st increase 103000 Mothly rent to 31 December 14 8583.333 17166.6667 100,500.00 1 year to 5 years Year 2 2015 Monthly rent to October 15 8583.333 85833.3333 annual rent after 2nd increase 106090 Mothly rent to 31 December 14 8840.833 17681.6667 Total rent yr 1 103,515.00 Source: Hanrick Curran audit file 31. 31experience. new thinking Hard coding Commonly seen on ad hoc spreadsheets. Typically involves a formula like: = C5 * (A36 + 1.03) 408 + 12 The reviewer can usually decipher that the 1.03 is probably CPI, but what about the other adjustments. A better way is to put the CPI number in its own cell as an input. Hard coded adjustments should also be avoided. If needed, build data entry cells for adjustments. Example of problem use of hard coding Source: Hanrick Curran client board reporting file 32. 32experience. new thinking Remote references A remote reference is a reference in a formula to cells that are remote from the worksheet the formula is on, either to another worksheet in the same file or to a different file. Remote references are difficult to review and prone to errors. We recommend they be avoided by using a links sheet in a workbook for all cross-file links. Formula within a workbook should also avoid remote references by gathering all needed data and then using the formula Source: Hanrick Curran client board reporting file Source: Hanrick Curran client board reporting file Example of problem use of remote references Example of corrected approach to use of remote references 33. 33experience. new thinking How big can the errors get? In January 2010, academics Carmen Reinhart and Kenneth Rogoff published Growth in a Time of Debt. Their report was widely cited by politicians as theoretical and research based support for reducing public debt and public spending. Later analysis reveals errors with the underlying spreadsheet analysis; countries are excluded from the average because of a range error. Great Brittan slashes spending by 10 billion, in response to the research and increase in debt following in the GFC. Source: Quartz website, http://qz.com/75119 Pasted from 34. 34experience. new thinking Reinhart & Rogoffs public problems Source: Australian Financial Review, 23 April 2013 35. 35experience. new thinking Allied Irish Bank US$691 m. Fraud AIB is one of the Irish big 4 commercial banks, parent of Allfirst Bank, based in Baltimore, Maryland, US. John Rusnak, committed a US$691 million currency trading fraud. Rather than pay $10,000 fee for a Reuters feed to the treasury compliance team (back office) the data feed to the VaR calculation was based on data from Rusnaks computer. The data was loaded into a spreadsheet which Rusnak manipulated to ensure that trading losses were otherwise hidden from the VaR assessment. Source: AIB p.l.c. SEC filing, March 12, 2002 Source: R. Butler, The role of Spreadsheets in the Allied Irish Bank / Allfirst Currency Trading Fraud (2009) VaR = Value-at-Risk 36. 36experience. new thinking Allied Irish Bank US$691 m. Fraud AIB SEC Filing: A simple check to see if the holdover figures were captured in the next day's trading activity would have caught this scheme. At least two points of failure: 1. Data in spreadsheets was open to manipulation 2. Compensating controls were not strong enough to detect the manipulation Source: AIB p.l.c. SEC filing, March 12, 2002 Source: Hanrick Curran research 37. 37experience. new thinking Enabling Fraud In summary, the inclusion of a spreadsheet in a reporting chain enabled hiding of fraud, especially without adequate compensating detective controls and reconciliations. A similar fraud occurred in a Brisbane company between 2011 and 2013, resulting in a $2.4 million loss to the company, related to overstatement of inventory balances (16% of PY reported inventory). Source: Hanrick Curran research Data spreadsheet Reporting Missing control checks and reconciliations 38. 38experience. new thinkingexperience. new thinking 38 Raymond Panko, University of Hawaii, has undertaken significant research into spreadsheet errors. Pankos research informs the classification of errors in spreadsheets. Error taxonomy and research 39. 39experience. new thinking Error research There is a significant amount of research into human error from fields as diverse as mathematics, programming, aircraft accidents, nuclear incidents, proofreading and linguistics. A key insight from these fields is that human cognitive processes produce the correct result nearly all the time but have a small inherent error rate that stems from the same processes that produce correct results. In other words, the way we actually think is the heart of the problem, not simple sloppiness. Source: Raymond Panko and Salvatore Aurigemma Revising the Panko-Halverson Taxonomy of Spreadsheet Errors (February 2010) p.4 40. 40experience. new thinking Mistakes, Slips and Lapses When working with spreadsheets, errors can be categorised as follows (Reason, 1990): Mistake an error in planning Slip an error during a sensory-motor action, such as typing the wrong number in a cell (e.g., $120,000 instead of $210,000) Lapse a failure in memory, usually caused by overloading the limited human memory capacity In terms of error detection, planning and memory errors that occur off spreadsheet leave little if any evidence for error detection. Source: Raymond Panko and Salvatore Aurigemma Revising the Panko-Halverson Taxonomy of Spreadsheet Errors (February 2010) p.5 41. 41experience. new thinking Error frequency Research from Allwood used students solving a mathematical problem. Error rates identified included: 327 errors as they worked 60% of errors were execution errors (slips and lapses) 83% of execution errors were spontaneously identified and corrected during work the result, execution errors only accounted for 29% of final errors Logic errors (mistakes) accounted for only 25% of errors, but low detection rates resulted in thes...