Introducing
Your new presentation assistant.
Refine, enhance, and tailor your content, source relevant images, and edit visuals quicker than ever before.
Trending searches
SAFe @ OBS/CCdata
PI 19Q4
Some Data
17/06/2019
PI-Planning 19Q3
Startdate: 30/09/2019
Enddate: 27/12/2019
#Sprints: 6 sprints (last sprint = 3 weeks = 09/12-27/12)
#Working days (Max) = 62 Mandays
PI-planning 20Q1: 10/12 & 12/12
Deliverables
11/12/2018
PI-Planning 19Q1
20/06/2018
PI-Planning 18Q3
Start Hannibal-ART
18/01/2018
(Without other OBS-teams)
Commitment Reliability = #Features delivered
TimeToMarket = #Features from Funnel -Done
Quality = #Incidents
ValueDelivery = #Business Score delivered
Business NPS = Score by Business
Team NPS = Score by teams
Teams:
Continuous Exploration
Continuous defining, refining and prioritizing of features
Solutions
Infra
ADAM
GDPR
Foundation
OLIM
19Q4
19Q2
18Q2
18Q4
19Q1
19Q3
18Q1
18Q3
Preparation PI-planning
25/09/2018
PI-Planning 18Q4
27/03/2018
PI-Planning 18Q2
including all OBS-teams
26/03/2019
PI-Planning 19Q2
24/09/2019
PI-Planning 19Q4
1) Teams & Backlogs
Demand
1) Central decision board for each type of scope
R:\Datakoepel\DI_PI\PI Commitments\Commitments 2019Q4
2) Prepared for future delivery trains
Team composition
Deliverables
- Demand <> PI-backlogs
- Moving target
- Contingency
- Definition Of Ready
- Budgetted
- Prioritized
- Work to the teams <> Persons to the work
- Reinitialization ART
- Up to the teams how further (too big, missing profiles, ...)
- Overrule possible (Level5)
- Not everyone contacted yet
Business Score @PI-planning
Business Score after Delivery
What is the overall business goal behind the committed features?
Purpose:
Validate Understanding of Intent
Focus on Outcomes Rather than Process
Summarize Data into Steerable Information
Indicator if Stretch or not
2) Prioritization
Not required
Expected outcome in terms of business value (e.g 20% gain)
Which criteria should be met before acceptance
Not required
Reason: Central decision board for each type of scope
Scored committed & stretch PI-objectives
Defined underlying features
Defined underlying (high level) stories
Handshaked dependencies
Data & Leads
bv: AP510 - P6 Lara - Dashboard
Adam
e.g.: 598 - Adam - P6 Privat Banking Marcher
Data & Services
e.g. CAPAFEAT-94 - Data Entry for EUC
3) Feature preparation