state of analytics: retail and consumer goods

State of Analytics: Retail & Consumer Goods GAURAV PANTEKN

The age of what-i-want-when–i-want it consumers requires building frictionless customer experiences.

Let’s step back to address the question of our timeHow can I continue to be relevant to my customers?

…anymore

The bar for a good customer experience is being continuously reset by players that might not even be in your industry (Amazon, Disney, Uber, WeChat, Apple, AirBnB, Tinder)

A great experience today is table stakes tomorrow.

Core = Technology + Insights

ROI94%

of retailers don’t know/ measure the ROI in analytics

OtherPriorities

Why?

How Much

14.6%CAGR (2016-20) for

BI/Analytics IT budget growth

11%CAGR (2016-20) for

BI/Analytics IT budget growth

Source: EKN Analytics in Retail Industry Survey, 2012 EKN Big Data in CG Study, 2012

Predictive

14%

Basic Reporting and

Analysis

68%

51%

Basic Reporting and Analysis

33%

InvestigativePredictive

16%

Investigative

18%

2012 Analytics Maturity:CG companies led retailers

Source: EKN Analytics in Retail Industry Survey, 2015

Predictive

16%

Basic Reporting and

Analysis

41%

45%

Basic Reporting and Analysis

InvestigativePredictive

15%

Investigative

18%43%

40%

2015 Analytics Maturity: Retailers are closing the gap fast

Who Else

47%of retail business users bought analytics software independent

of their IT Teams

23%Of CG business users bought

analytics software independent of their IT Teams

Where

RETAIL CONSUMER GOODS

FIRST TIMEMobile BIBig Data

UPGRADE Data

Visualization/Dashboards

FIRST TIMEData

Visualization/DashboardsPersonalization

UPGRADE

Enterprise BI & Reporting

CHANGE SUPPLIER

SaaS BI Platform

CHANGE SUPPLIER

Master Data Management

Still bringing a knife to a gunfight?

Amazon continues to be the gold standard for analytics across all consumer industries.

The gap between it and the industry is widening

8

Source: EKN Analytics in Consumer Goods Survey, 2016Source: EKN Analytics in Retail Industry Survey, 2016

RETAIL VS AMAZON CG VS AMAZON

AHEAD OF AMAZON

2%AT PAR WITH AMAZON

18%

AHEAD OF AMAZON


10%BEHIND AMAZON


80%

Source (2013:: Google patent records-EKN Research (2013). Some media reports have cited number of patents that Amazon has received to be 1263.

• Amazon is innovating faster than other retailers. Since 1994, Amazon has received ~1000+ patents to Wal-Mart’s ~*50

• Each business/service area has at least one patent (Trade-In, Subscription Service, Digital Media etc.)

• There has been a gradual shift in the focus of patents but there is continued focus on improving personalizationPersonalization/Recommendations -> Search -> Fulfillment - > Technology

• It has a large number of patents that cover the use of analytics and customer data to improve the business (recommendations, usability content, promotions, payment, sentiment analysis of reviews etc.)

A break-up of Amazon’s patents

Entity ~ No. Of Patents

Amazon Technologies 560

Amazon.com 180

A9.com 100

Kiva 100

Liquavista 60

IMDB 16

Alexa 13

Clickmarks 12

True knowledge 8

Junglee 3

Total 1052

Amazon uses its proprietary algorithms and patents to differentiate itself from the competition and create barriers to entry (1-Click checkout patent).

Culture of Analytics + Technology + Arsenal of IP

The 4 Pillars of Insights:Need to move along the insight continuum

(Source: EKN Frameworks )

1

2

3

4

5

6

10

11

12

7

8

9

Privacy

Mo Data. Mo Problems.

Mobile Social

(Source: EKN 3rd Annual Analytics in Retail Study, 2014 and 2015)

Top Data ManagementChallenges

#1 Data Organization

#2 Data Integration

CIO REPELLENT

Hype Resistant

Twitter: @gpantekn

The no spin zone: The reality of Big Data is that few like the term, and it’s currently the domain of a few first movers

Top 3 business challenges

Lack of Budget

Unclear ROI

Lack of resources

Source: EKN 4th Annual Big Data in Retail Survey, 2015; EKN Big Data in Consumer Goods Industry Survey, 2015; Consumer Goods 2014 Tech Trends Study; EKN Future of Retail IT Survey, 2015

5%Avg IT Budget spent on

Big Data Analytics

Value: Accuracy (n=all), Fast, Cheaper

4%Avg IT Budget spent on

Big Data Analytics

Don’t get caught up in the term. • There is no absolute specification of what Big Data is; each

enterprise must define what it is for them. • Ways to measure (data):

• Volume – How much • Variety - How different • Velocity – How fast

• Traditional Definition• The strategy, business processes, tools and technologies that pertain

to datasets whose size and complexity is beyond the ability of typical data- base software tools to capture, store, manage, and analyze.

(Source: EKN 3rd Annual Analytics in Retail Study, 2014)

• Big Data is a relative concept. • Think of it as a generational leap from your current analytics

capability that give you the ability to do a whole lot more from less than with a whole lot less.

(Source: EKN 3rd Annual Analytics in Retail Study, 2014)

Don’t get caught up in the term.

Source: EKN Analytics in Consumer Goods Industry Survey, 2015

1 Limited resources who can interpret the output of analytics tools

Lack of single owner for analytics

2 Absence of a clearly articulated analytics strategy

3

Retail & CG companies agree on the top challenges


RETAIL VS AMAZON

DATA QUALITY

9x behindDATA MANAGEMENT

4x behindTOOLS

4x behindSKILLS

4x behind

The gap with Amazon across dimensions is YUGE!

Annoying Orange 2010

A viral sensation that no one saw coming

Offensive Orange 2016

A viral sensation that no one saw winning

Well that was unexpected

Jun 16, 2015: Why Donald Trump Isn’t A Real Candidate

Jul 16, 2015: Two Good Reasons Not To Take The Donald Trump ‘Surge’ Seriously

Jul 20, 2015: Donald Trump Is The World’s Greatest Troll

Aug 6, 2015: Donald Trump’s Six Stages of Doom

Aug 11, 2015: Donald Trump Is Winning The Polls, And Losing The Nomination

Nov 23, 2015: Dear Media, Stop Freaking Out About Donald Trump’s Polls

Feb 2, 2016 Donald Trump Comes Out Of Iowa Looking Like Pat Buchanan

Data-Fails & biases happen to the best of us


RETAIL CONSUMER GOODS

TEAM SIZE (MAX)

312TEAM SIZE (MEDIAN)

15

TEAM SIZE (MAX)

125TEAM SIZE (MEDIAN)

3DATA SCIENTIST

~30%DATA SCIENTIST

~20%

Size of internal analytics teams

Build the skill pyramid. Don’t use data scientists for pulling data

Source: EKN Frameworks

Source: EKN Analytics in Consumer Goods Industry Survey, 2015

Pricing Improvements

Promotion Effectiveness

Customer Insights Needs To Be A Torrent Across The Enterprise

Demand Forecasting

1 Optimize Inventory Levels

2

Out of Stocks Marketing/Campaign Spend ROI3

Immediate focus areas

The coming of Retail’s Watson moment !

Merchandiser A

Merchandiser BWatson

Data is for machines. Insights are for humans.

Design for humans and not scientists.Let machines have their data and automate tasks.

Contact Me

•Gaurav Pant Email: [email protected]: linkedin.com/in/gpantnycTwitter: @gpantekn

THANK YOU

state of analytics: retail and consumer goods

Data & Analytics