The digital revolution will not be evenly distributed

I'm writing today about digital transformation, and starting with two of my favorite quotes.  The first, referenced in the title, is from William Gibson, the author of Neuromancer and other great sci-fi books, who wrote:  "the future is here, it's just not evenly distributed".  That is, we experience glimpses of the future everyday, and some places or companies are more advanced than others.

Mark Twain said that that history does not repeat itself, but it does rhyme.  I feel this describes the talk about digital transformation.  Please don't misunderstand me - I think the emerging technologies that support a true digital transformation are amazing, and have the power to provide more benefits to customers and to create more insights and more profits for companies than ever before.  I'm perhaps a bit jaded because it feels like we've been here before, but in an entirely different way.

Almost 30 years ago I was fortunate enough to be part of one of the first implementations of SAP (R/2) in the United States.  At that time, software applications were stovepiped.  There were financial applications, manufacturing applications and customer service applications but no unified, enterprise application that integrated systems and data across all the functions.  SAP changed that, taking the market by storm and changing our expectations about software solutions and data integration. 

When we would talk to clients about the investments and potential benefits of implementing SAP, we'd always look for the means to generate new revenues and profits as part of the benefit, but the truth was that most of the benefits were driven by automation, efficiency and cost reduction.  Strangely, however, in most instances SAP installations did not dramatically reduce employment - the jobs and roles simply shifted to higher value work.

I think some of the same phenomena are at work in digital transformation, but on a much larger scale.  In all honesty there is no one digital transformation "solution", but a host of tools, methods and applications to make a company more digital.  The funny thing about all of this is that the benefits aren't from being digital, but should result from becoming smarter, faster and more nimble.  We'll see if the digital tools and solutions create those benefits. 

This is about transformation

But let's not neglect the fact that "digital" transformation is really about transformation.  The digital aspect merely points out that new tools and new methods are mostly consuming or creating data, or integrating or using data.  But what's going to get transformed is the revenue model, the customer experience and ultimately the business model.  What many firms are going to discover is that you can't bolt new digital technology onto an outdated, slow and bureaucratic operating model and expect benefits.  New technologies and richer data will require companies to change how they operate, and right now many companies think that digital transformation belongs with the IT organization, because it is driven by data.

What's going to happen is that many of the underlying capabilities or tools will create more data, which will lead to new services, products and experiences, which can be delivered through new channels and create new customer relationships, which will lead to new business model opportunities.  The operating model of the business will need to transform at least as quickly as the implementation and use of the underlying technologies.  Most companies do not understand this and are not prepared for the amount of structural and business model change that is going to occur.

Why will this happen?  New data streams will create opportunities for new services, new experiences and new revenue models.  Increasingly physical products will be offered as services on recurring revenue streams rather than as one time purchases.  Products that were once valuable will be given away in order to extract data and monetize the data stream.  All of these factors will radically change existing business models.

This is about the data

Digital transformation is a two edged sword - it both gives data and consumes data.  Some applications, like IoT, will create massive amounts of data that must be gathered, stored and interpreted.  However, for that data to have meaning, other data must be acquired and appended.  Other applications like robotics or Augmented reality will require new data streams that must be created.  Many of these solutions do not yet exist and in many cases are specific to the task at hand.

Many companies face at least three significant challenges where data is concerned:

1. The data they have is noisy, inconsistent and incomplete, meaning that the existing data cannot be used effectively for digital tools like machine learning until it is cleaned and standardized.  Much of the historical data is not useful unless it is radically improved.
2. Most companies don't have a lot of experience managing the volumes of data that will be generated, or acquiring and ingesting other data that will enrich the core data streams.  Few companies truly know which data is important and which data is not important.
3. Most companies lack experience creating value from data.  This is the holy grail - creating revenue streams from harvested data.  Yet, value is still barely understood and the skills don't exist in most organizations to do this well.  Few companies have deep knowledge and experience monetizing data streams.  This concept is one of the most anticipated value propositions of digital transformation, yet probably will be one of the most elusive.

Back to the ERP analogy

If I could revert to the ERP analogy, then, we can make assessments of what is likely to happen based on past experience. 

In the early ERP days, many companies had imperfect or incomplete data when ERP was implemented, so SAP and other ERP applications were often implemented with only the minimum amount of data necessary and older systems were kept functional to refer back to.  I think there will be a fair amount of parallel operations as digital systems come online for the same reason.  This is likely to slow full digital adoption because of the costs of supporting new systems and maintaining legacy systems at the same time.

In the early ERP days, there were few companies with the internal staff that could manage the new IT technology, so large consulting firms grew in coordination with ERP companies. Accenture, Deloitte and others should benefit from large implementations.  The good news here is that we should have learned something from those implementations and should be smarter about how to go about installing and bringing the digital tools online.  Human capital will be at a premium.

However, and this is where there is a significant departure from the ERP model, digital transformation tools are not monolithic.  An ERP application might replace three or four legacy applications.  Digital Transformation, bringing online IoT, blockchain, robotics, machine learning, big data and other tools and technologies, will simply layer on a number of new and discrete technologies and data streams on top of the ERP/CRM platform.  In other words, rather than integrating and harmonizing all the data in one application, these tools and methods will create new data streams with different focus and different purposes, potentially requiring a new means to capture and standardize all of the data from all of the different digital functions.

And it's hard to get value from data until you normalize, clean, standardize and interrogate the data.

The implication here is that the existing IT structures in most organizations will not be able to manage all of this data, in all of these streams, to create meaningful value from the data in their current organizational structures and forms.

Fulfilling the promise of digital transformation

Let's go a bit further - what happens when everyone has been promised the ability to gain more insight into the data using machine learning, and everyone wants to interrogate the data coming from a wide variety of data streams?  What happens when many IoT devices go online and products start sending packets of data back to home base?  What happens when marketers and sales teams want to start generating new value from the data being generated?  And all of this has to occur while the company continues with its traditional operations, to fulfill existing products and services?

There is a LOT of change coming, and I worry that the digital tools, while they have tremendous opportunity and promise, will overburden legacy companies which are struggling to compete today.  Most companies are not very nimble or agile, not accustomed to big change, so it will be interesting so watch this unfold.  The biggest opportunity - more data and more value from the data - is also one of the biggest challenges given the state of existing databases and data capabilities today. 

From this analysis we can expect to see lots of very small digital transformation pilots, because companies need to learn how to implement these tools, how to gain value from them and most importantly how to manage the data they generate and use the data they have.  Digital transformation will be a spot solution for at least the next few years, rarely an enterprise solution unless supported by an enterprise application.  Machine learning, robotics, IoT, blockchain, augmented reality and other technologies are not enterprise applications, but meant for specific tasks, and will be implemented in that manner and generate data specific to those applications in the short run.