A banking implementation at the halfway mark
The client and every number in this exercise are fictional, made up for practice.
Background
A regional bank is moving to a new loan origination system. The implementation was planned at 2,400 hours over 16 weeks. It is now the end of week 8. The steering committee meets on Friday and wants to know whether the program is on track.
| Workstream | Budget (hours) | Planned complete by now | Actually complete | Hours spent |
|---|---|---|---|---|
| Setup and configuration | 600 | 60% | 70% | 380 |
| Data migration | 900 | 50% | 20% | 610 |
| Integrations | 500 | 50% | 40% | 240 |
| Testing and training | 400 | 35% | 40% | 160 |
| Total | 2,400 | 1,390 |
The data migration team reports that the bank's loan records contain more errors than expected, and every batch needs manual correction before it loads.
Your task
- How much work was planned by now, how much has been done, and what has it cost? Is the program ahead or behind, and over or under budget?
- Where is the problem, and how sure are you?
- Estimate the hours to finish under two assumptions: the rest of the program performs like the first half overall, and only data migration keeps its current pace.
- What will you recommend to the steering committee, in five sentences?
One way to approach it
1. Planned, done, spent. Work planned by now (in budget hours): 600 × 60% + 900 × 50% + 500 × 50% + 400 × 35% = 360 + 450 + 250 + 140 = 1,200 hours. Work actually done: 600 × 70% + 900 × 20% + 500 × 40% + 400 × 40% = 420 + 180 + 200 + 160 = 960 hours. Hours spent: 1,390. The program has done 80% of the work it planned (960 ÷ 1,200), so it is behind; and each hour spent has produced about 0.69 hours of planned work (960 ÷ 1,390), so it is over budget.
2. Where. Data migration has produced 180 hours of planned work for 610 spent, about 0.30 per hour. Every other workstream is close to or better than plan: setup 420 for 380, integrations 200 for 240, testing 160 for 160. The problem is concentrated in one workstream, and the team has told you why: source data quality.
3. Two estimates. If the remaining work goes the way the first half went overall, the program finishes at about 2,400 ÷ 0.69, or roughly 3,475 hours. If only data migration stays at its current pace, the other workstreams need their remaining budget (180 + 300 + 240 = 720 hours) and data migration needs its remaining 720 hours of work at 0.30 per hour, about 2,440 hours. Total: 1,390 spent + 720 + 2,440 = 4,550 hours. The second estimate is the more honest one, because it follows the cause.
4. The recommendation. The program is behind and over budget, and almost all of it is in data migration, because the bank's loan records need manual correction. At the current pace, the program needs about 4,550 hours, not 2,400, and the 16-week date is not achievable. We recommend a two-week data quality sprint led by the bank's lending operations team, with our support, to fix records at the source before migration resumes. We will bring a revised plan and cost to the next steering committee, with options to phase go-live by loan product. Strong answers also note that the bank owns its data, so the fix needs a decision from its side, and that the estimate should be re-run after the sprint.