Digital transformation is complicated. Peel back the onion you’ll discover layers for experiences, technology, teams, leadership, culture, value.
Industry experts have various do’s and don’ts for pursuing digital transformation, but the goals are usually the same: Build a better business by enhancing digital capabilities so you can drive revenue, make customers happy, and stay competitive.
To achieve this, companies are embarking on all sorts of initiatives. Things like product recommendation engines, proactive customer service messaging, up- and cross-selling algorithms, Internet of Things, device messaging, social media, highly targeted ads, deep learning and production models for scoring and classification, and many others.
What seems to be somewhat missing from the conversation, however, is the data transformation you first need to achieve to support a successful digital transformation.
Digital transformation is about building (and learning how to operate) better engines. But data is the fuel for the engine. Feed the engine low quality fuel full of impurities and at best it will sputter along. Feed it the best fuel available, and it’ll give you top performance.
What is Data Transformation?
Data transformation, at the simplest level, is making sure that your data is de-siloed, easily-accessible, and built of records that are stable yet flexible, retaining their integrity while staying up to date..
When your data is clean, organized, and reliable, it unlocks a range of other benefits.
Data gets centralized and democratized, and brands have a single source of truth for who their customers are, what they want, and how best to reach them.
IT, Analytics, and Marketing departments reach across the aisle to collaborate on common goals using shared information, as opposed to operating in their own silos, being unaware of parallel silos, or using disparate information.