This is second part of my post on Master Data Management, using well-known Amazon.com to illustrate the value of managing and exposing reference data about key enterprise assets such as customers, products or suppliers. See also part 1 for the first two talking points on Customer and Product Master Data.
Third, Amazon builds trust through information. This was key to drive the success of its marketplace and more generally to Amazon’s “long tail” approach: when you visit Amazon searching for a product and find it, there are very few chances that you face an out of stock situation. But obviously, Amazon wouldn’t be able to support the costs of having those millions of products in their inventory, and that is why then opened their catalog to third parties. In 2013, more than a billion units worldwide were ordered on Amazon from Marketplace Sellers, and analysts estimate that Amazon marketplace now represents more than one third of Amazon sales.
This marketplace clearly brings value to customers, but this comes with a challenge: how can customers trust a seller that they’ve never heard of, and have no experience related to his reliability? Trust comes together with the “Amazon Seller Rating” that Amazon highlights when you’re about to purchase the product. If you have experienced buying through Amazon marketplace, you know that Amazon always contacts you to rate the supplier once the product has been delivered. Through that important process step, Amazon engages you and therefore drives your perception that those ratings are trustable. Once again, information is impacting Amazon’s growth.
So what can we learn from this? First, it shows the value and power of managing deep, shareable and trustable information about your key assets – customers, product and suppliers in this example – and then linking it tightly to your processes – customer facing processes in this example. Those data driven journeys may seem like a long and winding road, though: although Amazon manages customer identity across all their customer facing processes since the 90s, most companies aren’t able to do that twenty year later, and very few software solutions are delivering this “out of the box”. Look at customer one-to-one personalization for example: today, most companies manage their online interactions as clickstreams or unknown visitors, rather than as ongoing journeys with known or soon to be known customers. Ironically, because they know dealing without unknown visitors is not the best situation for an efficient sales process, they use artifact to “know the unknown” and are a result generally raise privacy concern from their customers that feel that there are being tracked on their behalf. The way Amazon uses customer identity and customer data across online transactions appears to be a much more transparent and win-win approach when dealing with online customer interactions.
The remaining question is when should you consider that as a best practice rather than next practices that only some pioneers have learned to deal with? Indeed, pioneers have shown that data driven approaches can drive competitive differentiation. But in industries that have been early to be hit by digital transformations, such as media, hospitality and travel, or retail, it has become as well a matter of survival.