Illustrative engagement. A representative scenario showing how we approach this kind of work in professional services. It does not describe a specific client; outcomes are described qualitatively.
Industry overview
What is shaping professional services
Consulting, legal, accounting and advisory firms win on reputation and relationships. Client feedback, thought leadership and steady lead flow keep them growing.
- Thought leadership builds credibility
- Client feedback improves retention
- Lead generation is becoming more digital
Client background
A chartered accountancy firm, working in Mumbai. This is an illustrative engagement: a representative scenario showing how we approach this kind of work, not a named client project.
- Organisation
- A chartered accountancy firm
- Sector
- Professional services
- Team engaged
- IT & Development
- Services
- Custom business applications, Data analytics & dashboards
Client challenge
Compliance deadlines for many clients were tracked manually.
Research objectives
- Deliver on the brief: practice management for a CA firm.
- Define requirements and success criteria the solution would be tested against.
- Deliver a reliable, secure solution the team can run and extend.
Target audience
Scope: Practice system.
Audiences we typically reach in professional services
Clients and former clientsProspectsBusiness leadersPartners and referrersProfessionals and staff
Geographic coverage
Coverage: Mumbai. Market: India.
- India
Research methodology
An iterative delivery approach: discovery, design, build and test in short cycles, with the client reviewing each step.
- 1Brief
- 2Task tracking
- 3Deadline dashboard
- 4Insight
We built a system to track tasks, deadlines and staff workload.
Custom business applicationsData analytics & dashboards
Sampling strategy
- Users and stakeholders from every affected team took part in discovery workshops and acceptance testing.
Data collection
- Requirements were gathered through workshops, process walk-throughs and a review of existing systems and data.
Data quality & validation
- Peer code review on every change
- Automated and manual testing
- User-acceptance testing with the client
- Release checklist and rollback plan
Data analysis
- Usage and performance monitoring after launch
- Defect and support-ticket trends
- Process time before and after
Key findings
- Deadlines need systems, not memory.
Recommendations
- Build on the core insight: deadlines need systems, not memory.
- Track adoption and support tickets, and plan the next release from real usage.
Business impact
- Missed deadlines became rare, and partners saw workload at a glance.
Impact is described qualitatively.
Deliverables & next steps
- Cleaned data file and data tables
- Interactive dashboard
- Deployed solution with documentation and handover
- Support and maintenance plan
- Repeat the measure after changes are in place to track progress.
- A natural follow-on question: which channels bring good leads?