Technology, Data & AI
Data & AI
Most change, transformation, M&A, M&A integration, separations, revenue review and generation, cost cutting programmes start with data collection and review. Nearly all programmes in today’s world start with good data collection, integration, analysis and understanding of those combined data sets. We team up our specialists from each practice with our Data Science & AI experts and you, to give an improved view of your world faster using our AI. Noting there are now external datasets that might be useful for this analysis. This multidisciplinary approach can produce faster better reviews and results.
Business Agility
- Expand agile from technology teams to the wider enterprise. Agility focused on people, not frameworks.
- Change mindsets and behaviours with a change journey co-created with your team. No cookie-cutters applied.
- Build and nurture your own culture for the organisation.
- Deliver the right value at pace for colleagues, for clients and, for society.
Data Capability
- Data Capability for Digital Change
- Introduce full stack “data pods” to uplift internal data team’s capability.
- Establish a data capability that can provide actionable insights-as-a-service.
- Propel business growth and create an insights based decision making culture
- Data cleaning-as-a-service using our AI powered engine, prepare clean data sets in half the time.
CIO Office
- Evolve the CIO office to be the engine room for a modern digital business.
- CIO cockpit providing a holistic view of the organisational rhythm
- Increase the transparency across the portfolio of initiatives and flow of value from outputs to outcomes.
- Improve the business management aspects of running a digital and technology function.
Start-ups and scale-ups
- Mentoring and support to review your strategy and business design.
- Product management as a service with market testing, validation and product management.
- Assess roadmap and prioritise against revenue opportunities
- Business design, lean operating models and partnerships, Product-as-a-service model.
- Pre-revenue and early stage investment.
Data
- Data Strategy, Transformation, Integration, Migration
- Data Solutions Architecture
- Analytics Solutions
- Data Platforms and Architecture Frameworks
- Carveouts, Separation
- Master Data Management
