A few weeks ago, we published the first part of our article on omnichannel, which came as a result out of an interview with Duncan Avis, Customer Enterprise Lead at Global KPMG Connected. We said that according to one of the latest KPMG studies, companies successful at omnichannel are also successful at eight core capabilities which imply connecting the front, middle and back offices (see the image below).
In this second part of the article, we would like to touch upon the technical side of their success. In other words, what are the technical prerequisites for enabling these eight capabilities?
It's not that companies tend to lack certain IT systems; at least, usually, they don't. Quite on the contrary, one of the questions at the KPMG study was specifically around the technology in place. All sorts of systems have been named — marketing analytics, marketing automation, in-store and sales solutions, contract and order management, billing solutions, even workforce management and product innovation management solutions.
But what Duncan and his colleagues noticed was that the companies that said they do get their return on investment — in other words, are successful in their omnichannel efforts — have enterprise-wide data management and enterprise-wide analytic capabilities in technology.
Data-centricity leading to consumer-centricity are two key factors to being an omnichannel Business, or as Duncan calls is, "omni-business" as opposed to just omnichannel. That being said, one needs to keep in mind that the data-centric approach presupposes agile data integration and smart data analysis.
How important the data analytics tools are going to be for businesses show the answers of the KPMG interviewees. While data and analytics were named as the third important area of investments currently and within the next 12 months, "it was the one area that had the largest increase going forward," says Duncan, explaining these insights as:
Data integration tools are often mentioned almost in passing in this regard, yet they do play an important role in collecting data from various sources in the front, middle and back offices, and feeding it to the data analytics systems. Data integration solves the rather classic problem of having disconnected, channel-specific systems in place, which do a good job in their own closed environment, but fail completely when used together with another channel.
Let me give you an example to prove my point. Duncan shared it with me when talking about integrating the front, middle, and back offices, but I think it fits perfectly into the data integration topic as well. Many times, because they were delivered by channel, product information management tools used for online have the schemes that are different to that of the core ERP systems used in stores.
Now, imagine you buy something online and you want to return it back to a store.
