Readiness Of Enterprise IT For E-Commerce

Krishnan Subramanian, Head - Digital IT, RaymondAn alumnus of Great Lakes Institute of Management, Krishnan is responsible for all digital initiatives covering areas such as e-Commerce, data analytics, apps eco-system, in-store experiences, process automation, cloud adoption and many other areas.

In the last 4-5 years, we have seen many large brands adopting e-Commerce as a sales channel of choice in India. The contribution of e-Commerce through own website & market-places to overall revenue has already touched double digits in categories like consumer electronics, while it is fast increasing in categories such as fashion, large appliances and kitchenware. Apart from e-Commerce market-places' help in marketing & promotion, the prominent reasons for the rapid adoptions are:

• Exponential distribution reach without having to go through the process of signing up wholesalers/distributors/franchisees
• Convenience of market-places managing courier & logistics
• Availability of detailed analytics related to customer preferences, buying behavior, drop-offs, and others
• Ability to rapidly liquidate old stocks
• High control over the quality of catalog & merchandising

While rapid adoption of e-Commerce has been a huge boon for the brands, it has also added a lot of stress on the enterprise IT systems. For most brands, IT systems are geared towards an offline sales model where the inventory flows through the whole distribution network before selling to the customer. Consequently most ERPs are geared towards a pure B2B approach for warehouse management, financial reconciliations, and others. However, with the advent of e-Commerce, these same systems are now being modified to cater to B2C selling to customers also.

In my experience, below are some areas where brands face a lot of struggle while adopting to e-Commerce and are consequently opportunity areas for IT teams to help grow the e-Commerce business.

Most sellers' warehouses are created to fulfill offline B2B orders to distributors, franchisees, stores, and others. For such order fulfillment, packing & dispatching is done in bulk and achieving truck loads efficiency is an important criteria. However, for e-commerce, each individual order has to be picked, packed as per market-place requirements & dispatched separately with different courier partners. Here, efficient `first
time right' order fulfillment is the primary criteria.

e-Commerce order fulfillment efficiency can be drastically improved by building algorithms that work in con-junction with the warehouse management system and help in dynamic binning allocation during in-warding and provide flexibility during dispatch. There are some e-Commerce oriented warehouse management systems available that fully integrate with market-places, courier partners and ERPs so that the entire flow from the customer placing the order to the courier partner delivering the product can be tracked from one dashboard. The next level of efficiency in the e-Commerce warehousing operations can be brought in by deploying robotic sorters that reduce points of failure in dispatch operations.

e-Commerce orders give a plethora of structured data that can be used to identify market trends & patterns

Financial re-conciliation
The e-Commerce market-places operate in different models such as B2B, B2C, sell or return, outright sale to recommended sellers, and others. All remittances done by the market-places to the brand have deductions such as commissions, logistics cost, payment gateway charges, penalties, and others and these also dynamically vary during sale periods. Additionally, different taxation scenarios become applicable depending on the operating model and locations. In such scenarios, having a clear view of outstanding from each market-place and calculating the e-Commerce channel P&L and cash flow becomes a very cumbersome activity. These issues can be effectively addressed by having a clear strategy to manage master data and credit availabilities related to agents (market-places) and distributors (preferred sellers). It is also highly recommended to map the different e-Commerce sales scenarios completely in the ERP and provide different pricing procedures, tax codes and seller codes. Third party add-ons are now available that directly integrate the market-place's remittances to the ERP so that automatic reconciliations and settlements are triggered during remittances.

Product Cataloging
Correct product information and display of complete catalog in the market-place websites play a key role in both increasing the e-Commerce sales and reducing the returns. Adding a process of quality check during dispatches helps in further reducing the returns. Cataloging & uploading the product information in each market-place becomes cumbersome as each market-place follows a different template and these templates also constantly evolve. Additionally, key master data elements are also different for each market-place. To address this, tools are now available that integrate with the ERP to pull the product master, enhance the catalog and share it with the market-places in their prescribed templates. They also dynamically change the catalog templates when the market-places modify it and provide suitable dashboard features to give a bird's eye view of catalog readiness.

Customer Analytics
e-Commerce orders give a plethora of structured data that can be used to identify market trends & patterns. An analytics engine that runs on the combined e-Commerce data and offline sales data can provide deep insights on customer behavior, product sales velocity, geographical distribution, logistics costs, and so on. This can be used to improve all aspects of business including production & offline sales.

The above highlighted points are the quick wins that any enterprise IT team can take to help the organization embrace & simplify e-Commerce. As the e-Commerce business matures and starts becoming a meaningful sales channel in the organization, then the next wave of IT initiatives focused on the customer - such as CRM based customer segmentation, targeting approaches, and propensity models can be taken-up.