Sales Forecasting: Science or Instinct?
Recently, we had talked about marketing automation, a digital transformation in the field that involved both artificial intelligence and machine learning. Even Natural Language Processing (NLP) has come a long way, enough to change the content marketing game. But while marketing has shifted to a digital ecosystem, sales as a function remains largely people-centric.
With the advent of e-commerce, it is likely to change in the foreseeable future. Then again, the more complicated the product, the more people-centric a sale becomes. It’s largely due to buyer sophistication, which enabled consumers to become more informed about their need and product utility.
In a way, to survive, sales required the allied support of marketing – now more than ever before. The time for marketing and sales to work in silos are long past, and should such a division persist, experts conclude the eventuality of organizational failure.
But sales as a function isn’t entirely straightforward – there are those that acquire customers, those that nurture them, and others better suited to sales research among many others. Another critical function of an organization’s sales ecosystem is forecasting.
Digital Transformation in Forecasting: Good for Sales?
A good sales forecast is essential to business growth, but it’s historically relied on the human element. Yes, emotions and hunches could make or break an organization’s quarter. However, progressive companies have begun using big data and artificial intelligence to pervade this aspect of sales. At the same time, while several may infer this as a threat to their own jobs, forecasting succeeds only as a combination of both artificial and human intelligence.
How can we do this?
How Do You View Forecasting?
Without logic backed by science, forecasting often falls into becoming either overly optimistic or drastically pessimistic. Both scenarios impact company growth. AI enables a certain rigor and discipline to sales forecasting, using nothing more than data and facts to reach a conclusion.
But to put this perspective to an end – a correct prediction is great but being able to explain the logic behind the same is even better. So, how should we treat forecasting? For what it is – a science.
Jay Nair - Chief Operating Officer, Marlabs Inc.
As the COO, Jay has played an important role in accelerating the transformation of Marlabs into a digital services and solutions provider. He spearheaded the Digital360 initiative, which offers a complete suite of digital services across industries. Jay’s broad and varied business experience and skills helped Marlabs incubate NexGen technologies that provide outstanding business value. He also played an important role in transforming the company from a small group of 15 to more than 2,300 employees globally, growing into a $100 million company.