How do we digitize and automate our processes, and where do we start?
Ranks processes and decisions by the value of digitizing or automating them and by how feasible that is, then sets build or buy and the operating model to run it.
What you receive
The use cases to launch first, build or buy for each, the business case and the roadmap.
Each process and decision placed by the value of automating it and the feasibility of doing so.
When to open it
- Competitors automate processes the company still runs by hand.
- Your technology team runs AI pilots without a business case.
- Technology spend grows with no link to the strategy.
What the project covers
- Inventory of processes and decisions by value at stake
- Feasibility: data, technology and the change required
- Build, buy or partner for each use case
- Operating model: ownership, skills and governance
- Investment, business case and roadmap
What your team brings
- Process maps with volumes and cost
- Systems map and data inventory
- Technology budget and current projects
- Results of earlier pilots and automation projects
- Strategic plan and investment limits
In your report
- Exhibit 1
A heatmap ranks processes by value and feasibility
Each process and decision placed by the value of automating it and the feasibility of doing so.
- Exhibit 2
The rollout roadmap sequences use cases by value and readiness
The use cases in the order to launch them, with the investment and the owner of each.
Where it applies
- Banking and lending
Where should we apply AI first: credit decisions, fraud detection or client servicing?
The volume of decisions in each process, the cost of an error and the data we already hold.
- Asset and wealth management
Which parts of client advice should our wealth managers hand to AI, and which should they keep?
The time advisers spend per client, the suitability rules each recommendation must meet and what each wealth band expects.
- Industrial goods and manufacturing
Where on the shop floor should we apply AI first: quality inspection, maintenance or production planning?
The cost of defects and downtime today, the data our machines already record and the skills on each line.
- Automotive and mobility
Which software and connected services should we build ourselves, and which should we source from partners?
What drivers will pay for after the sale, the engineering talent we have and who controls the vehicle data.
- Energy and utilities
Where should AI change how we run the grid: maintenance planning, demand forecasting or outage response?
The cost of each process today, the sensor and meter data we hold and the share of the spending the regulated return covers.
- Telecom and media
Which processes should AI take on first: network planning, advertising sales or content production?
The cost and volume of work in each area, the data we hold and the rights attached to our content.
- Travel, tourism and hospitality
Which steps of the passenger journey should AI handle, from booking to rebooking after a delay?
Contact volumes by step, the cost of each disruption and what passengers expect from staff.
- Public sector
Which citizen services should we move online first, and where can AI support caseworkers?
Demand by service and channel, the citizens who still need in-person help and the quality of our data.
Start with this engagement
Write to hello@tacitude.com with the project you have in mind, and we frame the engagement with your team.