Build versus Buy: 5 myths and realities (part 3)


Over the last couple of weeks we have been canvassing the issues in that age old debate about whether an organisation should use their existing resources to "do it themselves".  This week we look at Myths #4 and #5.  Check back next week for the sum up on what this means to you. 

Myth #4: We have people to build this in-house

In the vast majority of cases, it is quantitative analysts alone that are tasked to undertake internal build projects for energy organisations. With such a responsibility, these analysts are unfairly expected to be the “master of all trades” and, as a consequence, the scope of functionalities for risk and valuation tends to have a narrow focus and is often not useable for other groups in the organisation.

For a successful internal build, an energy organisation needs to employ a diverse range of separate skill sets to successfully specify, build, test, and maintain on an on-going basis, a comprehensive risk and valuation application. Individuals with specialist knowledge on pricing assets and valuation algorithms, financial engineering, database management skills and user interface programming are all required. It is rare for all these skill sets to be available with one organisation, let alone 1 or 2 individuals. Such a scenario seriously hinders the ability to develop successful applications in the appropriate context.

In our experience, the typical profile of the in-house build team for most energy organizations is an individual, or two, with an advanced technical degree (maybe a Ph.D) in an area like physics, or some kind of engineering discipline. They are typically a few years out of university, don’t have a background in financial engineering, or stochastic optimization, have never developed a commercial software application and have no prior experience of developing user interfaces (outside of XL) or linking to databases. They rarely – if ever – socialise their models and algorithms outside of the organization, and their only knowledge of financial contracts and physical assets is what has been picked up ‘on the job’. As a consequence, compared to the development of commercial software applications, such as Lacima Analytics, the level of IP developed is often akin to where we were over 10 years ago.

Myth #5 – We can get away with spreadsheets

Many in-house application build projects still involve the use of spreadsheets. Such an approach exposes energy organisations to regulatory scrutiny and reputational risk due to the high probability of more errors occurring in calculations. In addition, credit rating agencies and banks are demanding greater rigour, and tighter business processes, than are afforded by spreadsheet based solutions.

Errors in spreadsheets have caused a large number of significant economic losses

Problems associated with the use of spreadsheets for risk and valuation analysis also include unwanted time and costs to resolve issues, inconsistencies in risk metrics and valuation figures between front and back office due to the use of disparate models and the inability to effectively integrate results across multiple applications such as ETRM and accounting systems. It is well documented (see for example the European Spreadsheet Risks Interest Group website) how errors in spreadsheets have caused a large number of significant economic losses, including many for energy companies.

Check back next week for the sum up on what this means to you.

Risk Markets Technology Awards 2019 - Lacima Pricing and analytics Commodities RiskTech 100 - 2019 EnergyRisk Software Rankings Winner 2019