Where to Start with Digital Transformation?

Digital Transformation is the ability of an organisation to remain competitive.  By using new technologies more effectively than their competitors, this leads to greater market share, lower price points, improved product and/or service quality and constant innovation for clients.  But where do you start?

This article is designed for medium to large organisations that want to know how to do this.  I’ll draw on my 20 years of experience as an enterprise and solution architect with DXC technology. I was fortunate enough to help a range of clients which I can now couple with my knowledge as a trainer, across the 12+ courses that I now run.

Click to open the infographic below to see a snapshot of the steps to take to perform a digital transformation successfully.


Here is my list of key steps in order:

Do you have questions with these steps?  Contact our awesome ALC Training team!

Why Governments will be Disrupted?

Digital transformation is the process of cultural,  technological and thought leadership innovation, that is required to ensure businesses remain competitive, relevant and able to survive.  Let’s break that down and explain what I mean.

Click on the image below to see ALC’s range of courses that can help with your digital transformation journey:

Cultural Innovation

This means allowing people within a business to develop and grow, by learning in a safe environment.  We often call this Failing Fast.  This helps to foster a culture within an organisation, that moves away from:

And move towards:

You can only innovate when you allow people to take risks.  But in concert, you need to provide tools and an environment for continual fast feedback.  This includes:

All these concepts and learnings appear again and again in many of the cultural change courses I run:

Click on the picture below to watch an awesome video from our DevOps Foundation course, covering Spotify Engineering Culture:

Technological Innovation

This means adopting the latest technological innovations, to help business leaders learn and act quickly.  There are many examples:

It’s no surprise that at ALC, we’re focusing on these key technological innovations:

Click on the diagram, below to see an awesome video from the Enterprise Big Data Professional course on why we use Hadoop over SQL when dealing with Big Data:

Thought Leadership

This is the most critical.  Leaders are the people in a company that pave the way for new things.  Just like in music, they are the avant-garde, breaking new ground, failing fast and leading by example.  They are skillful coaches that bring all their people with them on the journey.  They lead through:

You’ll find these leadership traits are exemplified in the following courses for leaders:

The diagram below shows you the Scaled Agile Framework, of SAFe for short.  Click on it and you’ll be taken to the FREE clickable version on their website:


If you have ever worked in a government department or a local council, there are very few examples of these digital successes.  Why?  I believe many leaders of governments, whether they be the lord mayor of a council or the elected minister, fundamentally do not understand digital disruption.  They believe it is a phenomenon that only affects commercial entities and is not relevant to them. And the ones that do try and embrace digital disruption, don’t focus on cultural change, with leaders not leading by example.

Unfortunately, it is extremely relevant.  I believe governments will be disrupted, just like every organisation in the world will be disrupted.  Charities, councils, regulatory bodies, none of them are immune.  In fact, they are the entities that are most at risk of being irrelevant.  Why?

Because for every government service, there is are much better ways of delivering, by adopting the key tenants above and embracing digital transformation.  This means, if enough people do not see the value in government services, they will protest, they will resist taxes and want to live in a place where the services are incredible. 

We’ve seen trailers of this movie before:

Click on the diagram to show you how you digitally transform your government organisation using SAFe:

Check out my latest conversation on “Navingating Digital Disruption” on the New York hit show, #AskTheCEO with Avrohom Gottheil:

How Does Modern Musical Composition Echo The Trend of Big Data

I was very fortunate in 2011 to be awarded a Leading Edge Forum Grant to perform distinguished research on In-Memory Data Grid technologies (IMDG).  At the time, the term Big Data had not been coined, or at least I had never heard of it.  The 3 months of intensive study and research for the CSC Leading Edge Forum, now known as DXC Technology, lead to a path of self-discovery and a realisation of what was really happening in the data space.  Here is a link to the brochure showcasing my work: 


Big Data is now defined as the problem space, relating to the cleaning and analysis of huge data sets, resulting in a series of recommendations, a roadmap and/or defined business outcomes.  It’s further described by using the 4 V’s:

Based on my research, and because of my classical / jazz composition background, I see Big Data slightly differently.  You see when I studied musical composition at the University of Wales and the London College of Music, I learnt that the most talented composers and performers had been using the same system for around 500+ years. 

Sounds remarkable, that a single system would pervade for so long, but it’s true.  We call it tonality, or in laymans terms we use keys and scales in music.  When we learn to play a musical instrument we learn all the different scales and all the different keys.  Examples include C Major, D minor, B flat major or C# minor.  This is why there is much emphasis on practicing scales and chords.  This system is called the tonal system and is still strongly used in pop music culture, especially in the pop music charts.

Now…at the turn of the century, between 1900 and 1925 a group of composers emerged, that are now called the Second Viennese School.  And what they did was remarkable.  They pretty much started to reject the use of the tonal system, that had served mankind well for 500+ years and created a new form of music called serialism.  Simply put, that is music that does not have a tonal centre, a key or is not strictly part of a scale.  We describe this as atonalism.  To the untrained ear, it would appear that the notes seems to be random and dissonant.   This is what atonal music, using serialism composition can look like.  

You’ll see that every note on the top stave is never repeated and every note on the bottom stave is also never repeated.  This ensures that no note takes precedence and stops us perceiving any form of tonal centre, or tonality.  Below is a short video explaining serialism, if you’re interested in learning more.  


This new school of serialism, led by Schonberg, Webern and Berg, was mirrored in the art and fashion worlds, through the abstract art movement, with Jackson Pollock being the most famous.  Below is an example of Pollock’s work:

So what the hell does this have to do with Big Data, I hear you cry?

Well Big Data is a great analog of this short history lesson in modern musical composition theory.  We’ve been using relational datastores for 30 years, and apart from the emergence of a few exceptions, the most popular datastores have been SQL based, conforming to relational database theory.  These datastores are commonly known as relational database management systems or RDBMS.  Think of relational database theory as musical tonal theory.  It’s worked for a long time, so why change it?  Examples of RDBMS include Microsoft SQL, Oracle and SAP.  With a relational datastore, we store data in tables and these tables all relate to each other in a schema.  Below is a simple example:

There are other rules that need to be implemented in order for a relational datastore​ and these include following the ACID principles, and rationalising the structure using normal forms.  Here is a good article outlining relational database theory:


Then companies decided to rethink the storage of data, to help solve new, complex problems.  The challenge with relational datastores is that they are great at storing customer information and financial information, but are not very good at processing and storing millions of records, that are unstructured, with 1000s of additional unstructured data items being thrown into the mix per second, with varying levels of data quality.  Basically relational datastores are not built to cope with Big Data.  They tend to be much slower, reliant on ACID principles, and are not optimised for handling unstructued or semi-structured data.  The diagram below outlines ACID principles in an RDBMS architecture:

The first well known company to use non-relational datastores en-mass was Napster.  They created a peer-to-peer music sharing network in the early 2000’s and used distributed hash tables to link up the data via central servers.  A distributed hash table is essentialy a key value store, which links a key (name of the song and artist), with a value (a link to the mp3 file).  This means it’s super fast and able to reference unstructured data very efficiently.  This provided a very successful, timely and ground-breaking music streaming  service, similar to Spotify today.  In those days Napster was later shown to be an illegal service, which has since reached agreements with record companies and artists.  Click on the diagram below to view a short video outlining how Peer to Peer networks operate:

In parallel we see Google invent Apache Hadoop technologies to deal with vast quantities of indexing material for search engines and the Big Data ecosystem grows expotentially from there.  We now have NOSQL datastores, In-Memory Data Grids and the list goes on.  Here is an article that best describes the key differences between the most common types of technology:  NOSQL, RDBMS and Hadoop:


Be aware that there is huge complexity and variation between different types of Big Data products.  The diagram illustrates this point, by outlining the current Hadoop suite of software tools, that can be utilised in a Big Data initiative.

Unfortunately we haven’t had enough time to cover Artificial Intelligence, Machine Learning and Deep Learning, which I’ll save for another blog post.  But these techniques, methods, approaches are all part of the Big Data movement.

If you’re interested in learning more about Big Data technologies, check out our new Enterprise Big Data Professional course: