The Data Lifecycle: Managing Data through Business. Ewan Willars Friday 27 February

Transcription

1 The Lifecycle: Managing through Business Ewan Willars Friday 27 February

2 ACCA s unrivalled global network 4,000 members & students in Canada

3 The changing role of finance and the CFO Traditional control & stewardship responsibilities Supporting strategic direction and creating value management and assurance Emergence of big data and the data-driven organization Extracting insights and value from data

4 10 Technologies shaping future finance 1. Social 2. Mobile 3. Cloud 4. Big data 5. Artificial intelligence and robotics 6. Cybersecurity 7. Educational systems 8. Payment systems 9. Virtual and augmented reality 10.Digital service delivery

5 The evolution of the profession?

6 What does tomorrow s accountant look like? The changing DNA of finance professionals 1. Technical skills remain essential but they are a baseline requirement 2. Deep commercial skills and business acumen are very important capabilities 3. Stakeholder mgt and strong internal and external relationships are essential 4. Strong communication and influencing skills need to be part of the toolkit 5. Being technological adept and understanding the value that data can bring is vital.

7 The emergence of smart finance Understand big data and its value to the organization Master the technology required to deliver value Lead a cross-organization data strategy Develop analytical capability that embraces big data create a unified data ecosystem Develop the skills needed within the finance team

8 barriers to success Too many legacy systems and manual workarounds Poor data collection Analytics - skills and application Fragmented data systems and technology Big data! Increasing opportunities but they are not being fulfilled = competitive disadvantage

9 % respondents Technology challenges facing business partnering % 43% 39% 38% 33% Multiple systems and manual workarounds Poor data quality A lack of sophisticated analysis tools Poor data descriptions Too much data * based on a global survey of 2000 senior accountants

10 skills needed for the next decade Knowledge of data extraction tools in the mining of business intelligence 72% Use of tools that support data modelling and analysis 69% * based on a global survey of 2000 senior accountants

11 The current state of play ERP systems Supply chain data Internal data Customer data

12 The current state of play challenges Reporting funnels Customer data Internal data Supply chain data Poor data integration

13 The current state of play challenges Supply chain data Internal data Customer data

14 Personal online activity Social media Wifi networks Big data sources Purchases and transactions CCTV Tax system Phone records Loyalty cards GPS and location services Search engines - Google Trends Health system Exhaust data the internet of things Transport system A company s supply chain Video clips Public records Personal use of apps Cloud platforms Market research

15 The -Driven Organization Create a unified data ecosystem Unified Ecosystem ERP General ledger Create a unified approach to data across the organization Develop data strategy and architecture in tandem Base this on a sound understanding of the data lifecycle Create a consistent view of data across departments Improve transparency between reported financial results and supporting transaction detail

16 Good Management The data lifecycle Manage business information throughout its lifecycle Understand where your data comes from, and how you extract value from it Theory developed in IT and research management Helps to manage big data effectively Deliver competitive offerings to the market faster and support business goals with less risk.

17 The Lifecycle Repurpose data Challenge collection processing analysis discovery reporting New challenges application

18 The Lifecycle Pressure points Repurpose data Are you making the most of your insights? Used to take decisions or justify them? Take it to the next level predictive insights and forecasting Challenge collection processing analysis discovery reporting New challenges application

19 The Lifecycle Pressure points Repurpose data Volume, variety and velocity of data collection needs to be targeted Consider new forms of data acquisition Challenge collection processing analysis discovery reporting acquisition strategy New challenges application

20 The Lifecycle Pressure points Archive dark data New revenue streams Repurpose data Purge Challenge collection processing analysis discovery reporting acquisition strategy New challenges application

21 The Lifecycle Pressure points Audit and assurance challenges Real-time reporting inside the business New external reporting forms New systems and technologies Increasing importance of non-financial data Valuation challenges Challenge collection processing analysis discovery reporting application

22 The Future: the data-driven organization Decreased operating costs by consolidating and simplifying IT architectures Improved transparency between reported financial results and supporting transaction detail A consistent, holistic view of data across financial functions and other functional teams Reduced business reliance on IT Detailed profitability and cost driver insights to improve customer, vendor and product profitability Agility - adapt quickly to market changes Aligned performance metrics to drive accountability and performance Evolve finance into a value-added analytic enabler to the business

23 The data-driven finance function A data-driven finance department has the following objectives: provide data leadership across the organization improve decision making across finance and other functional areas manage the ever-increasing regulatory reporting requirements enhance control and risk management capabilities improving cost efficiency and lowering the costto-serve.

24 Where can I find out more?

25 DIGITAL DARWINISM: Thriving in the face of technology change

26 100 DRIVERS OF CHANGE for the global accountancy profession

27 BIG DATA: Its power and perils

28 Enhancing competitive advantage through analytical insights Are you unlocking the value of your data?

29 Thanks!