State of Analytics: Retail and Consumer Goods
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Transcript of 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
0%AT PAR WITH AMAZON
10%BEHIND AMAZON
90%AT PAR WITH 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
Source: EKN Analytics in Consumer Goods Survey, 2016Source: EKN Analytics in Retail Industry Survey, 2016
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
Source: EKN Analytics in Consumer Goods Survey, 2016Source: EKN Analytics in Retail Industry Survey, 2016
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