It is no major news that organizations are consciously gearing up to capture a customer demand regardless of the source/channel of demand and then attempting to fulfill the same. Internet dot com sites, cell phones/ ipads or any other such mobile devices give the buyers the necessary platforms to capture and convey data from multiple points and attempting to move to a truly smart consumer-centric model.
While there is a lot of activity and discussions on the trends in the Next Generation Commerce solutions and how a multi-channel e-commerce (MCC) solution enables retail organizations to offer consistent services across virtually any customer touch point, the question that comes to mind is "Are Supply Chain Planning systems (both demand and fulfillment) in a state where they can predict and plan the increasingly volatile demand?"
While having the ability to capture a firm demand, irrespective of the channel undoubtedly is a great solution and is helping a lot of retailers in increasing their top lines, would it not be a better situation to be in, if one can anticipate buying patterns across channels & plan for this volatility in demand well in advance?
Retailers are currently riding high, reaping the benefits of using the MCC solutions and having the ability to meet or exceed sales targets. It would be a matter of time before, surpassing the newly set sales targets become the need of the hour. There are already discussions around MCC being a thought of the past and an emerging era of Agile Commerce. However both the situations, i.e. a matured MCC market and the Agile Commerce era seem to prompt for a better planning system; one that can predict the volatility of demand at multiple channels or sense and predict the demand at multiple customer touch points.
While the buying patterns in B2B scenarios are relatively more stable, buying patterns in B2C scenario's could have a lot of changes from one period to the next. To the best of my knowledge, forecasting solutions that are currently available in the market from well known ERP vendors or even the Best of Breed demand planning solutions are either based on Statistical, Regression based or consensus based models. However most of them do not carry the models for demand sensing and cannot predict how many customers would be visiting the kiosks, or how many would be visiting the websites and how many would be visiting the stores? More importantly, of all such visits at multiple channels, how many of such prospects would actually buy at each of these channels.
The primary input for the current forecasting solutions for demand planning is past or historical sales accompanied with firm independent and dependent demand inputs. While these can continue to be the prime inputs, the forecasting algorithms can aid a lot more if they can be changed to include the buying patterns of customers to predict better.
Larger businesses like Unilever and P&G have identified this gap and have implemented additional demand sensing solutions like those from Terra technologies to improve their responsiveness to current sales and/or reduce their forecast accuracy error over and above their demand planning solutions.
In this era, where the critical success factor of businesses lies not only in its ability to forecast and plan, but also being able to respond quickly to changes, it would make a lot of sense even for the software product companies to have demand sensing go hand in hand with demand planning and thus evolve the Next Generation of Supply Chain Planning products.
It would be interesting to get more insights & opinions on this. Do share if you have come across situations where you have seen these requirements or know about best of breed vendors or packages that are offering solutions in this direction.