5 common mistakes made by deep tech startups?

5 common mistakes made by deep tech startups?

The past two years had even overwhelming for the Indian startups. Looking at the change in the global startup positions, we’ll find that in 2021, India ranked 19th among the 100 countries that were included in the list of the top 100 startups in India. Besides, the Indian subcontinent was also ranked 48th in the Global Innovation Index 2020.

One of the major industries that India has been advancing in these recent years is the deep tech sector. With over 1600 deep tech startups launched in India between 2014-2019, the deep Tech market has been estimated to grow at a CAGR of 40%, which is indeed a tremendous boost to the country’s startup ecosystem. Besides, the capital investments for the deep tech startups have also increased parallelly. The venture capital investments for the deep Tech startups have reached $1.4 bn across 130 deals in 2021, according to Venture Intelligence’s data.

Yes, getting investments is a struggle indeed sometimes for some deep tech entrepreneurs and startups, but that is getting fast mitigated except for the funding winter that is nearing. However, another thing of grave importance that is required along with having a powerful team and scalable technologies is making the right decisions at crucial moments, and not repeating the mistakes.

India’s deep tech startups initially faced the problem of funding, but they now seem to be relieved of their anxieties because of the clear view of profitability that they can get now. This has made the moment fit for investors, entrepreneurs, and startups to focus on the tech ecosystem and build their businesses.

The internet is full of surprises, and with one click, you can get loads of information. The same goes for startup enthusiasts, who can easily get books, guides, and videos from all over the internet. It is very much imperative for startup companies to experiment, learn, and get their skills polished. They must have a process to deploy their tech solutions at a reasonable price. Besides, they must also nurture an attitude to learn, and think creatively about solving people’s day-to-day problems. However, what they need to avoid most is giving way to missteps.

The Maharashtra government has recently revealed its plans of setting up an INR 200 Cr women-focused fund in the early-stage deep tech startups. The Bangalore government, and several governments of other states, even the central government of India as well, are taking major initiatives to nourish deep tech startups from across the country. Along with that, well-reputed platforms like Sanchi Connect are building the stage for these deep tech startups in India so that they can remain connected with the VCs and angels from across the country, thereby building a convenient network that is viable and fertile for growth. So, with all these companies betting for the startups, it is their responsibility to detect the mistakes they are making in terms of approaching the fundraisers or expansion of business, deployment of products and services, and more.

5 Common Mistakes that deep tech startups must avoid!

A deep tech startup that involves robotics, AI, and machine language is quite involved with customer-specific deployment. Now, at the same time, it is essential to note that with each passing second, technology is evolving. Here’s where the deep tech startups are failing to understand that they need to keep up with that pace. At present, their deployment environment is generally based on customers’ expectations, which is causing a tremendous backlog in their progress. In this scenario, they must understand the problems first, discover their mistakes, finding out solutions to them will then follow. So, to point out the most common mistakes, here we are with a list of 5 major mistakes that the deep tech startups of India should not repeat.

Not Collaborating with Researchers

Every company requires a separate team whose integral job is handling every bit of research necessary to create a well-established product or service plan. This should be the primary unit to start with. Here, the deep tech startups also need to collaborate with their research (R&D) team, support them, and learn from them, thereby working as a coordinated unit, which will help build the team and products. However, not collaborating with the team of researchers might lead to bigger problems for these startups and deep tech entrepreneurs really, which might also cause irreparable damage to the company!

Demanding High Funds at the Very Beginning

If the startup company deals with AI and machine language, they need to go through numerous rounds of experimentation and prototyping. Each of these phases includes testing and verifying results. Moreover, if the deep tech startup is related to healthcare, clinical trials must be conducted. Thus, the entire process requires heavy funding and expensive equipment, even in the earliest stages of seeding. In these scenarios, the deep tech startups in India have often come up with high funding requests from the VCs, most of which have been denied. They fail to understand that they have to gain recognition and need to earn credibility enough before they can demand such investments. Besides, the entrepreneurs also need to sustain and preferably lead, for a significant amount of time so that the market can know about them. So, basically, there are deep tech investors in India, which includes angels and VCs, who are willing to put their money in the business in return for equity, but asking for high funds is not going to bring them anything big right at the start.

Failing to Understand the Technology Readiness Level

Technology Readiness Level indicates the status of technology and in which stage the tech development is in. This signifies whether a startup can develop tested products and deploy them in the actual environment. Often deep tech entrepreneurs face risks due to complexities while deploying a solution because of the low technology readiness levels. The challenge is that if the Technology Readiness Level is low, then there are potential risks and the deployment also gets delayed. Thus, the deployment must be postponed until and unless the company is ready with an iteration that is fit to hit the market.

Not Developing Market-Required Products/Services

Unless the product is launched, it becomes difficult to understand whether the product is ready for the market. Thus, it becomes imperative to understand the commercial application and maturity of the existing customers based on the product deployment. Suppose a product is being launched in the Indian market, but the customers are not ready for it or are ignorant about it, then the entire process is much of a failed venture. Therefore, if the deep tech entrepreneur is working on a nonexistent product in the market, then the product must be aligned to the customers’ knowledge and their way of work. Besides, it also needs to essentially solve a problem, which will further attract the customers.

Not Connecting with Investors at the Seed Stage

deep tech entrepreneurs need to depend on the funds from VCs, and late communication with them can result in missed chances of getting the money. Usually, entrepreneurs think that after they get to form a brand or start gaining recognition, then they would approach the fundraising companies/investors. But, while they are wondering to turn things tangible, they seem to lose out on their precious time. Lack of deep Tech funds at the proper time can lead the company towards a dead end. Moreover, the funding process starts from the Pre-Seed/Seed stage, where one needs to present the idea, get approval, understand the market, and proceed. This is a long-term process, and only the early birds can get the best offers.

Deep tech startups must invest in innovation and efforts!

Deep tech is in its growing phase and has huge space to explore. For entrepreneurs, deep tech is no less than a world that is unfolding slowly in front of their eyes. Becoming a leader or thinking of becoming one is not easy. Yes, the entrepreneurs and the deep tech startups in India are bound to make mistakes. It is never too late to learn from the mistakes, but one must not repeat them. In India, VC funds have come up to invest in and support technological development that would lift the Indian economy. SanchiConnect is one of those helping hands who want to help a business scale up. So, as a deep tech entrepreneur, never make an irreverent business/revenue model, do not be afraid to face the challenges in the long run, and most importantly, make the least amount of mistakes.

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