April 4, 2024

LSA Digital Formula – Concept (with AI example)

Digital Transformation Is More Than Technology

True Digital value needs more than just cloud, code and apps – it needs secure, digital services that are usable by people.

According to a KPMG survey of 400 US tech executives (2023), 51% have not seen increased performance or profitability from digital transformation investments.  According to a McKinsey global survey (2023), 45% of value is lost during target setting/planning, 35% is lost during implementation, and 20% is lost after implementation.

Digital efforts can be off-track for many reasons, but it typically comes down to three root causes:

Three Typical Digital Problems

Focus on Better Services

Digital improvements need to be sustainable beyond implementation — so our focus should be on reliable, sustainable service delivery.  The high-level focus for service improvement should be across two layers:


…is anything that is the “ultimate reason” our organization exists – for example, in the case of a smartphone manufacturer, to deliver smartphone products and features that delight for our customers, or (in the case of a warfighting research lab) effective weapons technology that is rapidly transitioned into the hands of the warfighter.


…are needed for Business services – for example, to help with administrative applications & technology (e.g., finance, HR, etc) and operational applications & technology (e.g., integrated modeling/simulation technology platforms for weapons design).

For “Big Digital Transformation” results — both during, and to be sustainable beyond implementation — a balanced “Digital Formula”  can help make the technology work for us, instead of us working for the technology:

Such a Digital Formula makes improvements across key areas – helping people be more agile and leveraging lean, scaled technology investments that provide better, more secure User Experiences (UX) — while minimizing full-lifecycle costs (including maintenance and operations). This helps organizations deliver reliable, sustainable business & IT services “beyond the big Digital effort” – helping achieve goals over the long term.

At first glance, this is not unique. It is based on typical “people, process, and technology” approach, which has been around since the 90’s. The modern take on Digital Transformation is the injection of a secure UX and agility into everything, considering full lifecycle cost (e.g., not just “buying the software one time”).  After all, if services aren't secure, usable by people, and delivered in time to be relevant, then what is the point of big Digital Transformation investments?



To illustrate a Digital Formula approach, an organization wants to upgrade their Digital experience with Artificial Intelligence (AI) assisted equipment shopping, helping customers pick product configurations (e.g., mechanical equipment features).  This is a large organization that already has experience selling services on the web, but now wants to leverage data on customers to predict what they should suggest to key customer segments.

We might ask about:

  • Scalable Technology – We intend to integrate AI technology into our existing website.  Are there cloud-based AI services that allow us to architect & design flexible API's and a low-cost “starter package” that can scale up to a package with more reliability and features?
  • Secure UX – How can we architect & design a web-integrated AI solution is truly helpful for our customers and partners, and not just a “distraction”?  How can we ensure that any solution we release has built-in security to meet applicable laws, rules and regulations?
  • Lean Governance & Process – What high-quality data do we already have on our potential customers, and what process/technology will we use to collect missing data?  How do we ensure those processes for data collection are compliant with applicable data privacy laws, rules and regulations?  How do we support the AI technology's API service lifecycle and maintain reliability?
  • Agile People & Approach – How can we start with a small AI experiment, see results, and build something bigger?  How can we train our people and/or leverage partners to continuously improve and maintain these high-tech services?