Business leaders are now losing sleep over digital transformation. It’s probably the biggest concern for businesses of all kinds. But one of the first challenges they run into is the lack of clarity around what is really meant by the term, because these words mean different things to different people in a business.
At the most general level, digital transformation is when a company uses technology to disrupt itself and dramatically improve the customer experience. They do this to avoid having disruption visited upon them by an outside agent – whether that’s a faster moving incumbent competitor or some little company no one’s ever heard of. Depending on your role in a company, you’ll think differently about what that disruption will entail.
Marketing transformation
The most common is probably marketing transformation where marketers transition from traditional to digital tools and capabilities. Search, social, analytics, content, commerce, CRM, web, and mobile will all come into play. This offers the opportunity to capture and use all the insights that come with these digital practices: to understand customers better and market to them more personally and more effectively.
IT transformation
The next level is IT transformation, where the CIO and the technology organization begin to migrate infrastructure to the cloud and introduce “as-a-service” application models to make the company more flexible, scalable, and resilient. The aim here is to enable rapid response to changes, opportunities, and new business models.
Organizational transformation
Many companies are employing agile and lean practices in combination with technology to drive organizational transformation. This means breaking down silos and working in cross-functional teams that focus on moving fast, continuous improvement, optimization, and failing forward to deliver more value to customers. This also helps employees connect to the customer and their co-workers better.
Analysts and tech writers have done a pretty good job of covering these digital transformation topics and though there aren’t too many superstars yet, many companies have leveraged their advice to move well down this road. Other companies are a little slower getting started but they’ve begun. Still others have their head in the sand and are hoping this will all go away. But what will eventually happen is they will go away. Because transformation isn’t an option. It is an absolute requirement for survival in the current business environment.
Operational tranformation
But what about operational transformation? Transforming business process management (BPM), enterprise resource planning (ERP), and other internal day to day tasks and processes? These unsung activities – the daily work of regular employees – are what make every company function. They cover the bulk of company activity, representing an enormous opportunity for reinvention. Though questions and comments about the practice are starting to pop up in articles and forums, operational transformation is a severely neglected topic across most of the analytic sphere.
Automating busywork and removing minutiae from workers’ plates allows them to think about the customer, perhaps for the first time. It raises the level of employees to knowledge workers who drive more ideas and innovation. A better employee experience creates happier, more satisfied, more engaged, more productive workers. A streamlined company is less expensive to run which can translate to lower prices for the customer. Some roles can be repurposed to be more customer-facing, improving customer insight and customer service. In fact, I think you can draw a straight line from pretty much every internal improvement directly to a benefit for the customer.
There are at least three key enablers that have allowed the transformations that we’ve already seen and they’ll also power this next step:
The enablers are data, cloud, and artificial intelligence (AI)
Data from digital sources like CRM, transactional, 3rd party, and now the Internet of Things (IoT) has been growing exponentially to the point that increasingly sophisticated data management and analytic tools have been developed to derive insight from it. These will be applied to data collected from internal ERP, BPM, and task and process activities.
Web service wars between Amazon, Google, Microsoft, and others have driven down the cost of Cloud computing while making it more reliable and secure. The cloud providers also compete to offer value-added services in their Cloud contracts, including data management, analytics engines, and AI capabilities. Operational data will be moved to the cloud where it can be easily and inexpensively processed. (According to Panorama Consulting, more than 85% of these are still languishing in legacy local proprietary data centers.)
AI has exploded thanks to the power and affordability of graphics processing units (GPUs). These chips, originally developed to run the demanding algorithms of high-resolution graphics in game systems, have been produced in such quantity as to make them inexpensive. And it turns out they’re just the ticket for running AI algorithms as well. So AI has undergone a renaissance and is now everywhere.
AI machine learning will analyze the operations data and make recommendations about eliminating redundancies and what can be automated. AI automation will start to take over the busywork that has been increasing and driving down employee productivity for years. And AI and voice interfaces will provide intelligent agents that will serve most admin and secretarial functions for every employee, freeing them up even more to do the jobs they were hired to do.
Like three types of transformations before it, operational transformation will deliver another level of efficiency and differentiation to organizations of all sizes. By eliminating redundancy and busywork, this transformation will streamline business operations, empower employees, lower costs, and ultimately bring the customer experience to a new level.
