Hey Team,

Digital & AI is all the rage right now. You could argue that it has been the rage for the past 10 years however recent AI tech advancements have definitely expedited these conversations within the C-Suite.

I sometimes like to ask myself hard questions - What would I do if I was responsible for AI & digital transformation in an organisation?

This article from McKinsey provides a phenomenal framework that I would likely follow, so I thought it would be worth sharing it with you all.

It is inspired by their new book - “Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI”.

As always, I’ve done my best to pull out tangible, bite-sized insights that are easy to digest and implement within your organisation.

McKinsey Framework: 10 Tactics To Deliver Digital & AI Transformation In 2023

Why is this important? McKinsey research has found that whilst 90% of companies have launched some flavour of digital transformation, only 30% of the expected revenue benefits have been realised.

McKinsey has leveraged insights from over 200 large companies across multiple industries to identify SIX critical enterprise capabilities to facilitate successful digital & AI transformation:

Below, we’ve pulled 10 key tactics across the different enterprise capabilities that you can use within your organisation:

1. Business-led digital road map 🛣️

Tactic 1: Inspire & align the C-Suite 👩🏼‍💼

Take the time to establish a common digital language to ensure that all C-Suite members are aligned on the approach. Where possible, leverage learnings (good & bad) from other organisations who are more advanced / progressed on their digital transformation journeys.

Tactic 2: Identify the right “bite size” business scope 🍪

Some companies struggle from the start of their digital and AI transformation by getting the scope of the change wrong. They start too small—believing that implementing a few use cases will lower risk—or they spread bets and resources too thinly across an uncoordinated set of initiatives. Both approaches typically produce little value.

Successful companies, on the other hand, focus their efforts on a few important business domains, such as a production process or the customer journey, and transform them from end to end.

As many as 80 percent of successful interventions in struggling digital and AI transformations are based on re-anchoring the scope to spur a concerted effort against a few well-defined domains.

2. Talent 🧍🏽‍♀️🧍🏾‍♂️

Tactic 3: Build a digital talent bench 🛏️

No company can outsource their way to digital excellence. It requires an accumulation of digital talent embedded within your organisation - product owners, experience designers, cloud engineers & software developers. These resources need to work side by side with business experts.

The aspiration should be to have 70-80% of digital talent in-house, with 20-30% coming from outside the company.

McKinsey states that you should look to have “a healthy ratio of hands-on-keyboard-technologists versus managerial roles”. They advise to have a 4:1 ratio of “doers” vs “managers”.

Tactic 4: Revisit how HR recruits digital & AI talent 🚤

Many HR organisations are hampered by slow recruiting & onboarding processes, rigid compensation frameworks and outdated learning & development programs for digital talent. This is going to lead to fewer quality candidates being hired as they don’t want to work in these types of organisations.

McKinsey recommends establishing a “Talent Win Room (TWR)” which is primarily focused on finding technologists with the right skills to build and continually improve all facets of the hiring process - this team is ultimately a “continuous improvement” function within the HR team, who is focused on reducing dated processes.

3. Operating Model 🛠️

Tactic 5: Choose the best operating model to support your strategy 🕵️‍♂️

McKinsey identified 3 operating models that work best for digital & AI transformation leaders (see below). Each model adhere to two fundamental concepts which appear to be strong drivers of successful digital transformation:

Concept 1: Agile squads / PODs - These are small, cross-functional teams which work together to develop new products / services.

Concept 2: Aligned to user journeys - These squads / PODs work best when they are aligned to a specific user / customer journey OR are focused on creating a set of replicable assets / services that can accelerate the work of all other PODs (e.g. establishing a data lake).

3 Operating Models For Successful Digital Transformation

#1 - Digital Factory: A separate organisational unit where people work together to build digital solutions for the business units. This works well as it can be implemented relatively quickly without too much disruption to business units.

#2 - Product & Platform Model: This is an evolution of the digital factory which aims to embed the agile / POD working methodology into each functional business unit. It is not uncommon to see digital teams work in “agile” fashion across different business units, whilst other functional teams still operating in a waterfall approach.

#3 - Enterprise-Wide Agile Model: This model embeds the agile / POD ways of working across all functions within an organisation (tech & non-tech).

4&5. Technology & Data 🖥️

Tactic 6: Create a “Technology Toolbox” 🧰

Similar to how tradies have a set of tools that they work with, digital teams need proper tools to do their work - Product Owners, Designers, Developers etc.

It’s integral that access to the right technology is quick & non-intrusive. Teams shouldn’t have to speak with IT every time they need access to a piece of technology.

Tactic 7: Use APIs, without exception 🦾

Put in simple terms, developers are only as effective as their ability to connect systems & datasets together. Application programming interfaces (APIs) facilitate this by making cross-system data easily accessible. This removes barriers for developers when they are trying to build new products & services.

Tactic 8: Invest Into Data Lakes & Connectivity 🏊‍♂️

McKinsey states that as much as 70% of the effort involved in developing AI-based solutions can be attributed to wrangling and harmonising data. Poor data access (and quality) can severely inhibit A+ employees in their ability to deliver high-quality outputs.

Build reusable data products & lakes - McKinsey acknowledged that Agile teams work best when they’re either focusing on specific user journeys, or replicable assets. It is integral that you have dedicated teams working on establishing “data lakes” or “data products” that provides a consistent, clean & connected source of truth for data. Try to prioritise building data products that have the broadest application e.g. “single view of customer”.

6. Adoption & Scaling ⚖️

Tactic 9: User Adoption Is Just As Important As Development 🙅🏻‍♂️

Companies will often spend a considerable amount of time, effort (and money) to develop an awesome new product / service but fall at the final hurdle - implementation & adoption.

McKinsey recommends that for every $1 spent on developing digital and AI solutions, plan to spend at least another $1 to ensure full user adoption and scaling across the enterprise.

Tactic 10: Use OKRs to measure what matters 📈

It is critical that you are measuring the effectiveness of digital transformation. The real question though is - WHAT & HOW should an organisation measure progress.

McKinsey recommends connecting digital OKRs to operational KPIs, “tracking the progression of each pod in a disciplined stage gate review process”.

By connecting agile OKRs to business KPIs, it fosters cohesiveness across different functions of your organisation.

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