Capabilities, Sample Use Cases, Case Studies

Transcription

1 Capabilities, Sample Use Cases, Case Studies Core capabilities of Diaku Axon Visibility & Understanding Analysis & Alignment Control Measurability Collaborate on a shared understanding of the organisation and visualise your place within it Filter, explore, compare and evaluate - support business change and promote continuous improvement An integrated view of organisational accountabilities with the ability to facilitate and record decision-making Measure performance and progress across the business, identify focus areas for future improvement Use cases leveraging core capabilities The following sample use cases highlight how Diaku Axon s core capabilities combine to satisfy key organisational challenges. Use Case Visibility Analysis Control Measure Reference Data Standardisation Data Quality Measurement in Context Data Quality Standardisation Root Cause Analysis Accelerated Understanding The Lean Enterprise Current State Analysis Progressively build up Data Lineage Definition Standardisation Change Programme Optimisation Managing Regulatory Change Document Management Support Supporting Big Data Data (and Business) Governance Business to Technical Data Mapping Trace Regulatory Reporting Lineage Four case studies covering four of the above use cases are included here. Additional documentation and case studies available on request.

2 Case study : Reference Data Standardisation "We could never have have brought visibility and control on this scale without the structure and mandate of the data governance framework and function. All steps were forward there was no backsliding. Financial Services / Credit risk and risk weighted asset reporting A large bank was looking to optimise capital allocations under the Basel II regime across the group. Critical dimensions like product and asset segmentations relied on mappings of local value lists to standardised group lists with little visibility nor control around those. Lack of visibility and control over the mappings had resulted in the firm holding significantly more capital than strictly required. Targeting those areas with the highest capital allocations, product reference data lists were catalogued and semantics and ownership clarified. Mappings into the central lists were brought under change control and governance. Reference standardisation was part of a data governance function setup and rollout that ran for 18 months. The alignment of the high value reference data mappings took 6 months Product mappings were aligned avoiding ambiguous and overly conservative mappings. This resulted in an immediate drop in capital requirements and an overall better understanding of data and its provenance. Basel II capital requirements dropped with 300m EUR. Data governance capability and community was established that was leveraged going forward.

3 Use case : Accelerated understanding From the CEO of the division - My organisation was weighted down by data. When I started asking questions about data I almost never got a straight answer ; there was a total lack of transparency. The Data Governance team rolled out Data Insight (Axon) and brought to me a much clearer picture in around 4 months, and more than that, there now was a go-to-point and a process to building transparency around data. Change Management, Operations, Regulatory Compliance Our client had embarked on a huge transformation programme. Data was the number one challenge: there was no clarity about what data lived in what systems and what it was used for. Manual interfaces and desktop solutions were hidden from view. Projects were over-running with data related challenges cited as the culprit. Each project was fighting it own data battle with little collaboration or re-use. Each area was tasked with cataloguing the key data they used in the 30 major systems in the division. Business context (processes, projects etc.) was subsequently added to build a picture of how data was used. Preparation phase 6 weeks. Knowledge capture phase, including review & sign-off 16 weeks. 30 core systems were captured, along with another 75 related upstream / downstream systems data attributes were recorded across those systems, mapped to 700 distinct glossary entries. Over 150 processes were then overlaid on this view along with associated policies. This view was created and supported by over 250 stakeholders across the business. The shared view formed a clear baseline for the program of work. Understanding was re-used by the data governance team to bring stewardship to key business data.

4 Case study : Supporting big data We were confident that we were finding interesting results, but there were inconsistencies in the output that we couldn't explain. Understanding the origination and meta-characteristics of our data really helped us to refine and filter our analysis, bringing a result that we could use, and also easily play back to our business stakeholders Data Analytics A pilot study was underway looking at the value of big data and how it could help improve client retention. Data from a number of systems was taken and the correlation with account closures identified. On further investigation of the output, questions were raised about the validity of the claims made. A significant spend was brought into doubt because the data was not sufficiently understood. Metadata definitions were mapped to the data sources used in the big data analytics. In addition to the definitions, client and product coverage from sources was also captured. 4 weeks from start of engagement to mapping data used in big data experiment. It was identified that the coverage of the data supplied differed across systems, providing only a partial view of certain customer types. Additionally in some case customers information was incorrectly split into two or more accounts. With this information it was possible to exclude the partial records and add the missing cross-references to build complete records. Improved understanding of the inputs improved the quality of the output. The output was confidently used to inform decisions to improve customer retention.

5 Use case : Data (and business) governance "Our MRU codes were a real mess. Nobody wanted to own them. We started by getting the codes properly defined and sharing this information with MRU users. We were surprised at the difference it made bringing conversations into the open. With a shared way to look at the data and discuss our issues we made real progress with the support of the central governance team. Eventually we managed changes ourselves, and have now added more of our key data into Axon." Management reporting A key reference data list - management reporting units - was being poorly controlled. It was unclear who was using the list, the master source was a spreadsheet on SharePoint, and changes were largely uncontrolled Management reporting was misaligned preventing real comparison across business areas. Poor governance had lead to misuse of the data set to capture other organisational hierarchy information. The management reporting units were mastered in Diaku Axon supported by clear definitions and ownership. Stakeholders were added in defined roles, and workflow ensured consistent processing of change requests. Data was onboarded within a 4 week period after which controls and governance matured progressively. Immediate improvements from the visibility and control gained. Change requests were openly discussed and agreed among all stakeholders, and over time used to improve the quality and usage of the master data set. Effective collaboration solved a key challenge the business had been struggling with for several years. Efficiency gains in managing reporting alignment 2 FTE. Management reporting across platforms aligned without the need for manual intervention

6 Use case : Business to Technical Mapping 3 years into the integration of the two banks we struggled to have a clear view on which systems, interfaces and data items were in use by the business and which were not. Levering the information and business experts recorded on the data insight portal (Axon) allowed us to identify what had business relevance and rationalise the IT infrastructure accordingly." IT Asset Management After a prolonged integration of 2 banking entities it was not clear anymore which system components still truly had business relevance. Most of the staff originally involved had left and documentation was poor and hard to locate. IT was struggling to adequately maintain support levels. At the same time IT was expected to reduce costs based on the anticipated economies of scale. IT worked with the data governance office to catalogue the data items that still were in use on the integrated architecture. The business relevant items were subsequently mapped to the underlying technical assets. The initial cataloguing within the money markets and treasury business lines tool 4 months. IT was able to overlay their technical architecture with a business view to inform relevance and materiality. A structured dialogue was now made possible between IT and their business stakeholders, several IT assets were decommissioned or rationalised. In the initial phases of the effort several interfaces were decommissioned along with the decommissioning of a Oracle workflow system totalling savings of over 600k annually.

7 About Diaku Diaku has a unique take on Data Governance with a focus on collaboratively building a shared understanding of data within its business context. Diaku has the methodology, expertise and software for its clients to unlock value fast and work towards lifting the data burden once and for all.