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

ACCA’s unrivalled global network

The changing role of finance and the CFO

Supporting strategic direction and creating value Traditional control &

stewardship responsibilities

Emergence of big data and the data-driven

organization

Extracting insights and value from data Data management

and assurance

Emergence of big data and the data-driven

organization

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

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.

What does tomorrow‘s accountant look like?

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

Data 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

45%

_43%

39%

38%

33%

0 10 20 30 40 50 Multiple systems and manual workarounds Poor data quality A lack of sophisticated analysis tools Poor data descriptions Too much data % re spon dents

Technology challenges facing business partnering

69%

72%

Use of tools that support data modelling and analysis Knowledge of data extraction tools in the mining of business

intelligence

Big data sources

Purchases and transactions

Exhaust data –

©ACCA

The Data-Driven Organization

Create a unified data ecosystem

ERP

General ledger

Unified Data Ecosystem

• 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

©ACCA

Good Data 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

The Data Lifecycle

Pressure points

Challenge Data collection Data processing Data analysis Insight discovery Insight reporting Insight application Repurpose data

New challenges _Insight

application

• Are you making the most of your insights?

• Used to take decisions or justify them?

The Data Lifecycle

Pressure points

Challenge Data collection Data processing Data analysis Insight discovery Insight reporting Insight application Repurpose data

New challenges _Insight

application

Data acquisition strategy

• Volume, variety and velocity of data

• Data collection needs to be targeted

The Data Lifecycle

Pressure points

Challenge Data collection Data processing Data analysis Insight discovery Insight reporting Insight application Repurpose data

New challenges _Insight

The Data Lifecycle

Pressure points

Challenge Data collection Data processing Data analysis Insight discovery Insight reporting Insight application • Real-time reporting – inside the business • New external reporting

forms

• New systems and technologies

• Increasing importance of non-financial data

• Valuation challenges

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

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

DIGITAL

DARWINISM:

BIG DATA:

Enhancing competitive

advantage through

analytical insights

Thanks

!