Think BIG, Begin Small

Whenever I meet any budding entrepreneurs, one common question that comes up most frequently is around how to decide WHEN ARE WE READY FOR LAUNCH? Should we launch our product with the basic minimum features or should we add little more advanced functionality to our product or services suite before we actually hit the market. 

It compels me to ask them ‘What is the USP of your product or services suite?’ If you are ready with that basic USP feature in your product, YOU ARE READY. You are ready to hit the ground running. 

I call this approach as MVP (Minimal Viable Product) or MVF (Minimum Viable Features) approach. 

I always believe that first version of the product should ONLY have features that you anticipate should be used most frequently by your potential customers. This is specifically true for start-ups where you have limited budget and team size is small. Most of things in such start-ups are usually at experimenting stage and you would want to keep your expenses at bare minimum with maximum outcome from your product. MVF comes very handy when you know the worth of every penny you spend on anything during this stage.

Once you are in the battleground (Market), then it makes more sense to gather the feedback from the audience (Customers) on what improvements or changes are required. Keeping your constraints in mind, you can work on such feedbacks accordingly. This saves you from over engineering efforts on something which you were initially thinking would be most useful for your customer but your audience didn’t even feel the need of having those features.

Here are some quick wins of taking the MVP/MVF route:

Early Validation in Real Market (Smart Launch) - This approach helps start-ups to go for smart launch of the product where they can get early feedback from actual customers and learn from it.

Relevant Product Improvement - Since you are getting feedback from your actual customer/audience, you can make relevant and market required modifications in the product without spending much efforts on adding and unwanted new features. Ideally, it will help in reduction of iterations.

More learning with less Cost - This also leads to reduce your development cost because you would be spending your resources on minimal set of features.