Startups

Ways to Smartly Structure your Startup After You Have Conceptualized It

Rely on native intelligence, more than acquired intelligence, to structure your first ventures.
Ways to Smartly Structure your Startup After You Have Conceptualized It
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Senior Correspondent
4 min read
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Startup founding and building are basic side-effects of today’s entrepreneurship which has been witnessing the advent of smart solutions to mitigate at least a layer of issues plaguing Indian society. Now, if you are a wannabe entrepreneur or first-time startup owners with passion to cater to the vast majority through your models which are lateral yet very much business-oriented, then it becomes imminent that you structure your startup/business smartly from scratch.

Also, plainly founding and running a startup would not do the trick for you, in 2018 and beyond, as smart models, structuring, and unconventionality are the key attributes that are to be met by your ventures. In this regard, Entrepreneur India lists easy ways in which you could smartly craft and structure your startup whilst ensuring it gets quality mentorship as well:

Carry out virtual demonstrations internally

While you focus on building your startups (smartly), it should do no harm for you to evaluate yourself internally on aspects related to being ready to take the bigger entrepreneurial plunge. These internal evaluations could be carried out in the form of virtual executions wherein you could run a simulation of what exactly your products could deliver before you take further steps.

Virtual internal demonstrations are a potentially effective tool since you could clearly document your smart offerings whilst getting another opportunity at eliminating flaws.

“It is one thing to have a brilliant idea and be passionate about it, but if you cannot execute, it's as good as nothing,” states Thiagarajan Rajagopalan who is Founder and CEO at Tripeur that is a B2B travel management solutions provider.

Hence, you could analyze your capability to actually execute, through virtual demonstrations; this could serve as vital tools when you connect with equity investors and mentors. Also, through smart internal evaluations, you could also cross-check on whether the right cause is set. For carrying out these, you could assemble your team or even execute single-handedly (provided you do not have a team in place yet).

Learn, learn, and learn to unlearn

Now, your ability to absorb new qualitative aspects goes a long way in determining how your startup is structured. The more your models are designed to accept external aspects, the better structured your startup becomes; considering the fact that you could holistically eliminate the negative elements and keep the positive ones.

“Openness to iteratively learn and unlearn are important,” adds Rohit Kumar Pandey, Co-Founder and CEO at Bengaluru-based healtchare startup SigTuple.

Pandey seemingly strikes chords when he states that the ability to unlearn for entrepreneurs could be vital; which is true from a startup perspective. From these, it is evident that you could develop models to clearly differentiate strategies (rather than plainly working on assumptions). Once strategies are segregated based on business needs, the structuring process becomes all the more intuitive.

Reliance on “data” is always good

When it comes to startup structuring, data is always key. By data, it is not the conventional business facts and figures and the internal figures; but a holistic analysis of these. Technological aspects viz. Big Data, Predictive Analytics, and Machine Learning could come in handy for data crunching.

You would potentially place yourself in a position to predict outcomes of a number of strategies through data analytics, and hold good stead to explore areas of improvement. Your products could also be customized to suit individual needs.

“ML is well on its way to revolutionize cancer care by providing an analytical approach towards understanding cancer as a disease,” informs Yogish Bhatt, Vice-President at Manipal Prolearn. Now, Bhatt’s statement reflects on the potential which ML holds towards overseeing smart models ina societal aspect like cancer care.

Here, the takeaway is that ML relies on data and if you feed the right healthcare data to it, the technology could actually crunch data to present an analysis which could be applied towards developing services which you aim to offer via your startups.

Hence, the key is data and your ability to smartly collect data, it could also be through hardware such as sensors.

“Data is the buzzword today and use of Big Data to customize a more effective experience to meet customer needs and goals is the latest trend,” summarizes Pinkesh Shah who is Co-Founder and Director of Programs at the Institute of Product Leadership (IPL).

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