Data Strategy Session. #analyticsx. C opyr i g ht 2016, SAS Ins titut e Inc. All rights res er ve d.

Transcription

1 Data Strategy Session #analyticsx C opyr i g ht 2016, SAS Ins titut e Inc. All rights res er ve d.

2 Think Big, Start Small Data Governance in Maersk Supply Service Helle Lindsted, Master Data Manager Analytics Experience 2016

3 page 3 Agenda Background Setting the scene Introduction to Maersk Supply Service (MSS) MSS World The history of MDM and Data Governance in MSS People and culture Data Governance in MSS MSS Data System landscape and data volumes MSS Data Governance Framework Overview Key learnings Technology SAS Data Quality Advanced Data profiling Data analysis Data monitoring Business Data Network

4 page 4 Setting the Scene Business units in the APMM Group handle data and Data Governance in many different ways. This presentation is related to Maersk Supply Service only. Data Governance: Formalizing behavior around the definition, production and usage of data to manage risk and improve quality and usability of selected data.* Tools can support the goal of getting better data but can never replace management support, people and processes. *Robert S. Seiner, Non-invasive Data Governance, Technics Publications 2014

5 The APMM Divisions page 5

6 Maersk Supply Service at a Glance page 6 Established 1967 Offshore employees 1,250 Onshore employees 215 Subsea Support Anchor Handling Tug Supply Present fleet current vessels / Newbuilds 53/ 10 Platform Supply Local offices 8

7 We Never Compromise on Safety page 7 We strive for zero personal injuries also at the office

8 page 8 The History of MDM and Data Governance in Maersk Supply Service Pre Master Data managed locally on vessels, onshore and/or by APMM Group 2012 ERP project launch 2013 First draft of Master Data organization presented to SMT All Master Data entities defined and mapped in detail Data Governance framework approved by SMT Reorganization 1H2016 Data Governance for supplier data kicked off 2H2016 Data Governance for part data kicked off Reorganization

9 page 9 System Landscape Poseidon ERP MSS SAP HR Excel MAPS APMM Group Win-Admi

10 page 10 Data Volumes Supplier: 2670 records Customer: 560 records Master Data Entities Vessel: 130 records Part: unique part numbers Standard job: 920 records Sales contract: 700 records Purchase orders: approx per month Transactions Supplier invoices: approx per month Customer invoices: approx. 180 per month

11 People and Culture page 11 Mixture of seafarers and office people People Dynamic organization Less talk, more action Operating in an industry under pressure due to low oil prices Increased cost consciousness Culture Data traditionally handled by others (APMM Group, seafarers or third parties) Increased management focus on the importance and value of good data Strategic initiative to establish data-driven decision making Moving very slowly from aware/reactive to proactive on maturity scale

12 Virtual MDM Team MSS Data Governance Framework page 12 IT Governance Committee Direct or delegated representation Aligning Advising HR Integrated Solutions Business Services Vessel Management Sales & Market Development Executive Entity Owner Executive Entity Owner Executive Entity Owner Master Data Manager Driver & integrator of MDM Collaborate Monitor Inspire Business Data Owner(s) Business Data Owner(s) Business Data Owner(s) Master Data Specialist(s) Master Data Specialist(s) Master Data Specialist(s) Data Maintainer(s) Local Master Data Contact(s) Local Master Data Contact(s) Local Master Data Contact(s)

13 Data Governance Implementation Key Learnings page 13 Acknowledge that data is not the core business Be prepared to work hard to get commitment People Link roles to functions, not people Make friends with data ambassadors Be patient and flexible Do not expect that users know the processes and/or follow them Level of complexity must be just right Processes Be prepared to redefine processes on an ongoing basis Start small and build on your successes Do not expect to get it right in one go

14 Data Profiling page 14

15 Data Analysis page 15

16 Data Analysis page 16

17 Data Monitoring page 17

18 Business Data Network page 18

19 SAS Data Quality Advanced page 19 Visual UI for data profiling, analysis and monitoring Main Advantages No coding knowledge needed but may be combined with SAS code if desired Very powerful and easy to use out-of-the-box functionality of Quality Knowledge Base (QKB) Business Data Network showcases definitions and relations between terms and objects Set up data monitoring for all Master Data entities Move reporting to Visual Analytics Future Use Expand number of definitions in Business Data Network Customize QKB to extract part numbers from free text Use Master Data Foundations for Master Data pilot project for vessel data

20 page 20 Questions? Ph