a

Lorem ipsum dolor sit amet, consectetur adicing elit ut ullamcorper. leo, eget euismod orci. Cum sociis natoque penati bus et magnis dis.Proin gravida nibh vel velit auctor aliquet. Leo, eget euismod orci. Cum sociis natoque penati bus et magnis dis.Proin gravida nibh vel velit auctor aliquet.

  /  Project   /  Blog: Time for disrupting the Disruptors

Blog: Time for disrupting the Disruptors


The software development industry can be said to be the backbone of the digital transformation happening across industries in today’s day and age. However, for an industry that leads the redefinition of industries, it has struggled to transform its own processes! After a casual chat during which Vikram Bhatia, a software product professional turned entrepreneur, lamented about the enormous time taken by software development firms just to get to the point where they had the opportunity of showcasing their skills to the client who was looking for such skills, Manu Saxena, a Technology enthusiast decided to use innovation background to study whether it was possible to disrupt the industry’s client prospecting and positioning processes.

Data is the new drug

The study revealed interesting results; one of the big firms, GE is already using Data Science and within it, Machine Learning processes on their datasets to generate superior business intelligence — the process resulted in a 45% increase in the revenue from existing clients in a particular vertical. However, the software industry’s new leaders — the development shops splintered across the globe, don’t have either the bandwidth to own or access to such processes; paying off a team of Data Scientists to align its prospecting and intelligence processes to support its business development team is outside the budget of most of these firms and no Enterprise solution exists that addresses these concerns.

Creativity Is the Key

Business Development is a tough beast; it can arguably remain insulated from the cold substitution by machine learning because it is a relationship-driven business that is grounded in empathy and trust. The teams though will have to use Data Analytics to increase their productivity. Katie Ng-Mak, VP of Global Partner Strategy and Operations at HubSpot, ranks creativity high among the list of characteristics of successful sales reps and managers. And this creativity will have more value for the client if its focused at removing the obstacles that the client has, in other words the dev shop has to highlight its ability to remove the pain points. A plethora of information is routinely available to buyers. Access to information that helps the BD team create a specific solution addressed at removing the pain points and the ability of this team to effectively articulate this approach will increasingly become the differentiating factor.

How it can be done

Studying previous history of organizations across discrete data points and using these to predict their behaviour in terms of buying activity is what Data Science can achieve. Imagine a client who wants to address some or all aspects of its digital transformation. Chances are that it could be from any industry and can have needs in any process out of the myriad of processes that together complete the transformation. Now imagine if an enterprise solution could provide the software development shop specifics of this need along with intelligence points such as the technology that this client is seeking and the urgency that this client has with respect to this project; at the very minimum the outcome of this process significantly cuts down the current resources wasted in attending conferences or seeking references from current clients to make cold approaches, at the maximum it can lead to a pipeline that never exhausts!

Going Forward

Global IT spending was upwards of USD 3.5 trillion in 2018. It is common knowledge that a chunk of that money goes into the business development segment; even by conservative estimates, the business development segment will be close to USD 1 trillion. Interestingly, software development has also moved down the chain to development shops from the big tech firms which now concentrate more on the project conception and delivery, using the development shops for the development. This is so because the agile method of delivery is more aligned with the size of these development shops as it is for the need for clients to have a customized solution. This trillion-dollar development shop segment needs a solution that can help them optimize their BD budgets. The fastest growing Development shops will use their time and budgets in the right direction; increase the total number of pitches to the right clients and use the marketing dollars to create the corresponding right story. An enterprise solution that leads them to the right prospects will empower them to achieve these goals. Any consulting advice that can tailor the marketing effort and uncover the pain points leading to the development of the customized pitch can be even more valuable.

After Billy Beane won 20 consecutive matches with the Oakland Athletics and kickstarted the Moneyball effect, it wasn’t any more about whether data should be used for talent identification and team formation, it was about when the clubs will embrace the technology. Some started in 2002, the last remaining MLB club did so in 2017! Similarly, the use of such a data science driven solution is not going to be point of differentiation after a few years; but any development shop thinking of not using such a solution can surely consider itself simply delaying the obvious!

Manu Saxena and Vikram Bhatia are Co-founders of Scopify.ai, the world’s first Data Science backed full stack business development solution aimed to make the development shops around the globe realize their true potential. Manu, a CFA charter holder, has a strong financial and analytical background; this is his second technology start up. Vikram is a product manager and a serial entrepreneur coming to Scopify after his recent success with www.gopbj.com. Together they are leading the pathway for disrupting the disruptors.

Source: Artificial Intelligence on Medium

(Visited 5 times, 1 visits today)
Post a Comment

Newsletter