What should start-ups learn from the current Big Tech downfall?

What should start-ups learn from the current Big Tech downfall?

GUEST BLOG. After a total euphoria in the field of technology, we are now witnessing the rapid descent of the majority of large technology companies. Think of the acquisition of Twitter by Elon Musk, who is already talking about the possibility of bankruptcy, or the 11,000 employees who have lost their jobs at Meta, Facebook’s parent company, in recent weeks. Unfortunately, I could continue the list for a long time.

Now, what can we take away from this tech crisis? Here are three lessons we can learn from this situation.

1 – Forecast customer demand to help you choose where you will invest the money.

Big Tech’s cost structure was mismanaged compared to other industries, as hiring was no longer driven by demand and revenue potential, but rather by the desire to attract new talent. new talents, ahead of their competitors. In the field of artificial intelligence, many even claimed that the valuation of companies was directly linked to the number of PhD holders hired, without any link to the quality of the product or the company’s revenues. This competitive pressure to hire at all costs and as quickly as possible has led to a misallocation of resources for Big Techs and it shows in their profits!

Ideally, start-ups hire based on need, driven by customer demand. For example, the vast majority of venture capitalists will refuse to invest in a start-up that is looking to raise money to generate more demand before they have some market validation. This is what is called in the industry “product-market-fit” which is in itself the correlation between the product and the actual demand of customers to pay for this product.

Hiring a mass of talent, even if they are among the smartest on the market, without really knowing what you are going to do is highly likely to lead to failure or put you in the same situation as Big Techs who must quickly proceed to massive cuts. Consider, for example, Element AI, which for a while was perceived as the next unicorn and housed the greatest brains of artificial intelligence in Montreal. The problem: She was hiring all the time, probably thinking it would end up with great products. Despite all the talent that was there, the company never managed to create a product with real commercial potential and, after hundreds of millions invested (including a lot of public money),

2 – Create a detailed plan to reach your income goals

What is the best way to predict customer demand? It’s definitely having a detailed plan to achieve your income goals. Too many Big Techs have taken advantage of the low cost of capital as well as the pandemic without properly planning their revenue targets. Many companies have estimated their revenue growth based on “learning new behaviors” during the pandemic rather than having a plan in place to ensure revenue is met. This is the case of Shopify which, after seeing the very rapid increase in sales on its e-commerce platforms, had falsely believed that this trend would become a given and would continue after the pandemic. Result: she hired massively and made very optimistic income forecasts,

For example, at Connect&GO , we expect to double our revenues in 2023, despite the possible recession. This is a very ambitious goal and requires a lot of planning. It’s easy for the president to say, “we need to double our revenue next year,” but it’s much harder to plan how we’re going to make sure we hit the target.

It is also this exercise that allows us to quickly see if our hypothesis is really plausible, as well as to predict scenarios that could significantly affect the downside or upside of the forecast (for example: if in the first quarter, we do not have X revenues signed, our chances of reaching the target will be reduced by 50% and we will therefore have to take the necessary decisions immediately).

While it’s nearly impossible to perfectly predict how much revenue we’re going to achieve next year, having a clear plan increases our chances of achieving it, but most importantly: don’t do like Big Tech and wait that it is too late to take the necessary decisions.

3 – Recurring revenue models are more useful in downturns

A lot of the tech companies struggling right now aren’t based primarily on recurring revenue models. Indeed, if we think of Facebook, Twitter, Snap and many others, their main business model is online advertising and have almost no guaranteed recurring revenue. In the case of Shopify, in addition to the subscription to the platform (which helps them), another portion of the income is based on a percentage of transactions on its e-commerce sites. A drop in their performance will immediately affect his own performance!

Tougher economic cycles like the one we’re experiencing right now remind us why investors are so obsessed with subscription-based revenue models. Although value-based pricing models were beginning to gain traction and still make sense in many businesses, it is certain that in the coming months investors will again increasingly appreciate the certainty of recurring revenue.

So don’t do like Elon Musk and Twitter who are hastily trying to impose a recurring revenue model on their users, but rather think from the start how your project could generate stable, predictable and recurring revenue. It will greatly help you through any crisis!

From your side, do you have any other learnings or observations on the current downfall of big tech companies? Do not hesitate to write to me to give me your point of view

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