As per our previous concern on Technology Transformation, it’s time to be digital, but with digitization comes digital fragmentation, especially when you don’t fully understand what you’re doing.
Why?
Digital fragmentation increases the risk of IP/cyberattacks (which is one of your top risks) as each fragment presents its own unique weaknesses and opportunity for attack. Moreover, it explodes the tech execution support required and increases one of the largest barriers to organizational success.
Digital transformation is also a concern because organizations know we have reached the age of digitize or die, but the digitization project failure rate is at an all time high of 88%+ (and 95% if it’s AI-based for the sake of AI) and every digitization effort to date has just resulted in more digital fragmentation. (To the point that the average mid-size organization has over 600 SaaS subscriptions and some have over 1,000.)
Impact Potential
The impact potential depends upon the degree of fragmentation. How many software applications? How many different hosting platforms? How many data pools? The impact of data fragmentation can be low if there are a relatively small number of software applications, they are all AWS hosted, and there’s only one data warehouse/lake/lakehouse. Or it can be extremely high if there are 1,000 SaaS applications, they are hosted on half a dozen cloud stacks (AWS, Azure, Google, IBM, Oracle, and Salesforce), there’s a data warehouse/lake/lakehouse for each of the divisions, and so on.
Major Challenges/Risks
Cybersecurity
Every one of your SaaS applications provides an entry point into your organization if hacked. Every cloud provider provides multiple entry points if hacked. Your data warehouses provide a huge amount of data that can be used against you. These hack points are in addition to all of your internal servers / on-site applications, employee laptops and smart devices. An average organization these days is a cybersecurity nightmare and a hacker’s dream.
Data Integration
Chances are all of your applications have their own data models, own unique entity ids, and own standards for data access. Integrating your data across applications is a nightmare, forcing integration through data warehouses/lakes/lakehouses, which in turns creates a data replication and synching nightmare.
Data Maintenance
Not only is there the synching issue from the replication used to support data integration, but less used apps means there are less checks and updates for the critical data they are the master applications for, and data quickly becomes stale and out of date. And employees depending on that data and accessing it through the lake don’t know that, and can make bad buying and partnership decisions based on that.
Final Words
Managing digital fragmentation is not easy. In fact, it’s a nightmare because most organizations don’t have, and never had, Master Data Management (MDM) or a Master Data Governance (MDG) strategy.










































































