- It's all too easy for companies to fall into the trap of digital transformation becoming more of a buzzword than an effective process. After watching its first attempt fall flat despite sufficient funding, enthusiasm and energy, Sprint went back to the books and reevaluated its digital strategy, creating a data-first culture and mentality to eliminate the uncertainties associated with transformation and put the company back on track, according to Chief Digital Officer Roby Roy in a Q&A with McKinsey.
- To set up for this new culture, the company had to start with the "pipes and foundations," condensing data into a few locales and implementing a large Hadoop environment all the data could be fed into, according to Roy.
- Strategic hires were key to Sprint's success. The company carefully selected a head of business intelligence and artificial intelligence, which Roy said were the most important hires. Roy also culled a business lead for digital adoption and a digital DMP owner and worked closely with these professionals to make sure they were embedded in corporate structure and had the necessary tools for success.
A few years ago, just moving to the cloud was the biggest part of digital transformation. But today, being able to leverage a variety of modern technologies, from Big Data analytics to AI to cloud services, is necessary for digital success in the enterprise.
Embarking on digital transformation just for the sake of doing it, without a clear strategy and resources in place, risks wasting time and resources.
"We started using the phrase 'digital transformation,' migrated processes and tools to be more digital, and created a dedicated business unit, and thought we’d automatically see that transformation happen," said Roy, in the McKinsey interview.
But a rough start doesn't mean it's impossible, and Sprint offers an important case study of technology leaders recognizing a shortfall and taking the necessary steps to fix it.
With so many metrics to keep track of, the data aspect of digital transformation can be overwhelming, said Roy. So he and his team went back to the basics, starting with look-alike customer data and, over time, slowly layering new elements like demographics or location on top.
They were then able to take the insights derived from that data, overlay it with new information from its digital properties and use the new insights to better understand customers. By building out these customer profiles, Sprint began understanding its base better and had the resources to teach bots about more contextually relevant customer interactions.