Business cases are problematic to write, especially when really realizing the costs and doing a proper financial analysis or understanding all the business, geo-political, social and financial risks.
With cloud costs rising and without understanding the impact external actors and competition can have on disruption, it's critical that business case submissions are taking into account a broader more balanced view.
What is shockingly lacking in many funding business cases and ones for internal approval?
Many startups as well as VCs for the lack of due diligence (or pretending to have the right resources to do due diligence or relying on AI lol), do not get into the financials, the ROI and payback well enough. The believe currently is similar to dot com, where they say the old rules don't apply. Unfortunately, they do and they have always stood the test of time, despite fads. AI changes the game, but the not the rules of how these investments should apply.
- Market research, TAM, SAM etc is often not well researched or analyzed to the right level of detail at all. It's ridiculous to say a startup can capture 1% of a market that has a population of over a billion, like India/China, not unless it has some very strong viral signs on it. The research sometimes come from biased, non-independent sources, and is often what you want to hear rather than what you don't want to hear. I have seen references, saying PwC, McKinsey without even sharing the actual document, year of publication, title name etc. This shows that someone was just trying to justify and not point to the source and the reality and research has not hit them hard yet. Some firms have sources, but they just read it the way they want, not necessarily what the research was saying. Also bias, vendor reports are inherently biased, so are consulting firms trying to push either their services or a vendor alliance.
- Strategic positioning - the frameworks such as Porter's 5 forces and others are useful, but many fail to realize how they can be disintermediated, or there are factors that can challenge, eliminate you. Applying this kind of strategy analysis (there are many other approaches), gives you an idea of risk, how to mitigate it and perhaps think of product positioning and innovation better. This is sorely missed, in the enthusiasm and hate to say it the younger entrepreneurs who have not yet really got the real experience of leading a more global/regionalized function and the cultural and other nuances, such as regulatory you have to deal with. Where is the market for robo-advisor technology now? It has been replaced by GenAI agents, dis-intermediated a major player like Mambu right out of the market.
- CAC (Customer Acquisition Cost) is often not spelled out properly. It's also notoriously hard in a competitive market with a B2B component. The effort works if you have other factors right, such as marketing, outreach, enticements (legal please), lack of competition, differentiation (that is not marginal but extensive), flights, hotels, meals, scaling up the stakeholder value chain, internal knowledge of client procedures etc. A lot can go into CAC analysis and mature startups and others know how to measure it and where the gaps are. Sales and marketing costs need to be controlled and tied to outcomes and not be a run-away
- Operational costs are often areas where there are big gaps. Salary is the easiest component to be measured, plus benefits. Harder now, due to the disparity of cloud products/cloud apps/cloud databases and on-prem is the cost differentiation. Does having infrastructure/DevOps and certain upkeep maintenance costs outweigh doing it yourselves on-prem? How difficult in terms of impact analysis is it to make on-prem changes and then follow the impact to every system and database. Are your process costs, actually granular? Do you have IT metrics or process metrics that measure the task, activity, coffee breaks, average productivity per employee or even if automated, whether that automation is effective? Do you have enough analysis on your controls to see if KPIs/KRIs are being achieved? How much is this loss productivity costing you and is there a better way to control it?
- Innovation / research - some level of experimentation needs to be budgeted for, but unfortunately there sometimes isn't budgeting and if there is, then it is not tracked. IT developers, architects are notorious for spending time on some passions, pet projects, which they believe will add value to the company, but in reality there could be more urgent pressing problems. An uncontrolled data science team can often be a major cost driver.
- Feature costs - design, build, integration costs and an independent analysis given your tech stack whether this was simple to build or more complex. This cost analysis will then give you an idea on whether product management costs need to be contained or development costs.
- Waste - GenAI uses up energy, it also costs more. Yes it is easier and faster to do things on GenAI, but do you want it to cost you or your clients more when an alternative will do? For example Google Translate is generally free to low cost to use and has a high level of accuracy, but many now waste GenAI and don't think of the energy wastage, cost etc. use GenAI for where it really matters and where there are cheaper practical solutions use them. It's good for your baseline as well as your clients.
