The Future of Accounting:Towards 2020 The Predictive Accountant

https://www.slideshare.net/ssood/future2020Suresh Sood, PhD

suresh.sood@charteredaccountantsanz.com@soody

Vignettes in the two-step arrival of the internet of things and its reshaping of marketing management’s

service-dominant logicWoodside & Sood

Journal of Marketing Management Volume 33, 2017 - Issue 1-2: The Internet of Things (IoT) and Marketing: The State of Play, Future Trends and the Implications for Marketing

Useful Resources

Acuity 2017

Big data accounting-the predictive accountant

Tools and techniques of the predictive practice

Bit.ly/BigAgribusiness

Advancing Agribusiness: Big Data and Systems of Insight

Source: Tips and tools of the predictive practice, Sood (2017) , June/July Acuity Magazine & 19 June Accounting Daily

The Predictive Practice

Areas for Conversation

• What will the future look like?

• What is driving major change in our accounting?

• Why do we need to bother with big data ?

• What is big data?

• How do we ingest truly massive data sets?

• What are the use cases for practices ?

© Chartered Accountants Australia and New Zealand 2016

By 2020-22 :

100 million consumers shop in augmented reality

30% of web browsing sessions without a screen

Algorithms positively alter behavior of over 1B

Blockchain-based business worth $10B

IoT will save consumers/businesses $1T a year

40% of employees cut healthcare costs via fitness tracker

Strategic Predictions for 2017 and Beyond, research note

14 October, http://www.gartner.com/document/34715682017 Hype Cycle for 3D Printing , July, http://www.gartner.com/document/3388326

Gartner (2016/17)

8© 2017 FORRESTER. REPRODUCTION PROHIBITED.

Forrester Research, 2016

“As business is transformed by the impact of big data and big data analytics, so the role of finance professionals will change as well”

Ng Boon Yew Executive Chairman of Accountancy Futures Academy of the Association of Chartered Certified Accountants Executive chairman

More Diverse Associates

The ANZ Heavy Traffic Index comprises flows of vehicles weighing more than 3.5 tonnes (primarily trucks) on 11 selected roads around NZ. It is contemporaneous with GDP growth.

The ANZ Light Traffic Index is made up of light or total traffic flows (primarily cars and vans) on 10 selected roads around the country. It gives a six month lead on GDP growth in normal circumstances (but cannot predict sudden adverse events such as the Global Financial Crisis).

http://www.a http://www.anz.co.nz/about-us/economic-markets-research/truckometer/ANZ TRUCKOMETER

Statistics, Data Mining or Data Science ?

• Statistics

–precise deterministic causal analysis over precisely collected data

• Data Mining

–deterministic causal analysis over re-purposed data carefully sampled

• Data Science

– trending/correlation analysis over existing data using bulk of population i.e. big data

–Extraction of actionable knowledge directly from data through a process of discovery, hypothesis, and hypothesis testing.

Adapted from: NIST Big Data taxonomy draft report :

(see http://bigdatawg.nist.gov /show_InputDoc.php)

Data Science Innovation

Data science innovation is something an organization has not done before or even something nobody anywhere has done before. A data science innovation focuses on discovering and using new or untraditional data sources to solve new problems.

Adapted from:Franks, B. (2012) Taming the Big Data Tidal Wave, p. 255, John Wiley & Son

Data Science Algorithms

Companies are reimagining Business Processes with Algorithms and there is “evidence of significant, even exponential, business gains in customer’s customer engagement, cost & revenue performance”

Wilson, H., Alter A. and Shukla, P. (2016), Companies Are Reimagining Business Processes with Algorithms, Harvard Business Review, February

Variety of Data Types & Big Data Challenge 1.Astronomical

2.Documents

3.Earthquake

4.Email

5.Environmental sensors

6.Fingerprints

7.Health (personal) Images

8.Graph data (social network)

9.Location

10.Marine

11.Particle accelerator

12.Satellite

13.Scanned survey data

14.Sound

15.Text

16.Transactions

17.Video Big Data consists of extensive datasets primarily in the characteristics of

volume, variety, velocity, and/or variability that require a scalable

architecture for efficient storage, manipulation, and analysis.

. Computational portability is the movement of the computation to the location of the data.

Categories of Data Sources

1. Transactions

2. External Data (CA Kairos curated data and content packs)

3. Customer data (includes web/e-commerce site Google analytics)

4. Social media and online search data

• The data collected in a single day take nearly two million years to playback on an MP3 player• Generates enough raw data to fill 15 million 64GB iPods every day • The central computer has processing power of about one hundred million PCs• Uses enough optical fiber linking up all the radio telescopes to wrap twice around the Earth• The dishes when fully operational will produce 10 times the global internet traffic as of 2013• The supercomputer will perform 1018 operations per second - equivalent to the number of stars in three

million Milky Way galaxies - in order to process all the data produced.• Sensitivity to detect an airport radar on a planet 50 light years away.• Thousands of antennas with a combined collecting area of 1,000,000 square meters - 1 sqkm)• Previous mapping of Centaurus A galaxy took a team 12,000 hours of observations and several years - SKA

ETA 5 minutes !

To the scientists involved, however, the SKA is no testbed, it’s a transformative instrument which, according to Luijten, will lead to “fundamental discoveries of how life and planets and matter all came into existence. As a scientist, this is a once in a lifetime opportunity.”

Sources: http://bit.ly/amazin-facts & http://bit.ly/astro-ska

Galileo

Square Kilometer Array Construction (SKA1 - 2018-23; SKA2 - 2023-30)

Centaurus A

The following BigQuery query (note that the wildcard on "TAX_WEAPONS_SUICIDE_" catches suicide vests, suicide bombers, suicide bombings, suicide jackets, and so on):

SELECT DATE, DocumentIdentifier, SourceCommonName, V2Themes, V2Locations, V2Tone, SharingImage, TranslationInfo FROM [gdeltv2.gkg] where (V2Themes like '%TAX_TERROR_GROUP_ISLAMIC_STATE%' or V2Themes like '%TAX_TERROR_GROUP_ISIL%' or V2Themes like '%TAX_TERROR_GROUP_ISIS%' or V2Themes like '%TAX_TERROR_GROUP_DAASH%') and (V2Themes like '%TERROR%TERROR%' or V2Themes like '%SUICIDE_ATTACK%' or V2Themes like '%TAX_WEAPONS_SUICIDE_%')

The GDELT Project pushes the boundaries of “big data,” weighing in at over a quarter-billion rows with 59 fields for each record, spanning the geography of the entire planet, and covering a time horizon of more than 35 years. The GDELT Project is the largest open-access database on human society in existence. Its archives contain nearly 400M latitude/longitude geographic coordinates spanning over 12,900 days, making it one of the largest open-access spatio-temporal datasets as well.

GDELT + BigQuery = Query The Planet

Oil reserves shipment monitoring

Ras Tanura Najmah compound, Saudi Arabia

Source: http://www.skyboximaging.com/blog/monitoring-oil-reserves-from-space

https://nodexl.codeplex.com/

Airbnb Power BI App

Connecting Power BI with Massive Big Data

Big Data Use Cases for Advisory Practice

Forecasting (Financial) or predictive analytics using external big data sources e.g. Airbnb and Web/e-comm site

Investor deck for startups and early stage including financial reporting and potential e-commerce revenues

Cross border/interstate business expansion

Cost of Capital Estimates

Risk Management including reputation (use social media channels)

M & A

Fraud

Spend Analytics

Continuous Auditing and/or missing inventory e.g. via Drone

23© 2017 FORRESTER. REPRODUCTION PROHIBITED.

trillion

$862 billion

$19 billion

$397 billion

$1.5 the amount of USD spent online globally in 2016

North America

Latin America

Western Europe

Asia Pacific

$248 billion

Source: Forrester Research ForecastView Online Retail Forecasts

*Global figure comprises 27 countries: Argentina, Australia, Austria, Belgium, Brazil, Canada, China, Denmark, Finland, France, Germany, Greece, India, Ireland, Italy, Japan,

Luxembourg, Mexico, Netherlands, Norway, Portugal, South Korea, Spain, Sweden, Switzerland, United Kingdom, and United States

Rate based on CAGR 2015 to 2021

10.6%

12.3%10.3%

8.3%

11.3%CAGR

How fast eCommerce is growing globally

24© 2017 FORRESTER. REPRODUCTION PROHIBITED.

Data aggregated from IBIS World reports, 22 August 2017

Online tenure leads to more spending per customer

High engagement leads to more orders, more categories purchased, and more spend

https://www.quillengage.com

http://recount.com/recount-expert-financial-analysis/

SimilarWeb - visiondirect.com.au

Go

ogl

e Tr

end

s

Alexa - visiondirect.com.au

Language on Twitter Tracks Rates of Coronary Heart Disease, Psychological Science, January 2015

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The findings show that expressions of negative emotions such as anger, stress, and fatigue in the tweets from people in a given county were associated with higher heart disease risk in that county.On the other hand, expressions of positive emotions like excitement and optimism were associated with lower risk.

The results suggest that using Twitter as a window into a community’s collective mental state may provide a useful tool in epidemiology…So predictions from Twitter can actually be more accurate than using a set of traditional variables.

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Sherman and Young (2016), When Financial Reporting Still Falls Short, Harvard Business Review, July-August

Sood (2015), Truth, Lies and Brand Trust The Deceit Algorithm, http://datafication.com.au/

New Analytical Tools Can Help

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Deception Algorithm

(1) Self words e.g. “I” and “me” – decrease when someone

distances themselves from content

(2) Exclusive words e.g. “but” and “or” decrease with fabricated

content owing to complexity of maintaining deception

(3) Negative emotion words e.g. “hate” increase in word usage

owing to shame or guilty feeling

(4) Motion verbs e.g. “go” or “move” increase as exclusive words

go down to keep the story on track

http://www.analyzewords.com

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“The honest answer is this: The accountant of the future might not be an accountant at all. Career paths and internal structures will change dramatically”

…a new type of "analytics" accounting professional is evolving and joining

existing practices. Initially, these individuals may well not have CA credentials

but are productive from day one if they possess an analytical mindset with an

ability to utilise relevant data tools and tech to gain insights from accounting or

more broadly business information.

At the same time, the individuals with existing data science or analytic skills

have the opportunity to compliment such skills with accounting skills through

bridging style conversion courses or accounting boot camps for data analysts or

data scientists.

The future is impossible to predict. However one thing is certain :

The company that can excite it’s customers dreams is out ahead in the race to business success

Selling Dreams, Gian Luigi Longinotti

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