Mid sized companies dont have sensors and machines spitting out big data, but they have lots of data from traditional sources like CRM, ERP and Billing software. How do you use this. Some techniques, examples and case studies from other industries to get your creatives flowing
4. How it influences decision making
Big data has been used to confirm or refute conventional wisdoms held by an enterprise
5. SME’s, Big Data and Analytics
Doing it
Some Case studies and Tools
Who are we
Canada Post analytics
showed that the risk of
dog bites is higher with
home delivery compared
to community boxes
Companies will shift
their future investment
away from IT-developed
reporting solutions
toward business-user-led
analysis solutions.
6. Do you have big data
Characteristics of big data
7. Data sources; big and small
ERP CRM
RFID
Network Switches
Billing
CDR
M/c
Sensors
Social Media and Pancreatic Cancer
8. Evolution of the Dataperson
I know the answer to all my problems and
really don’t need any more data: I didn’t
need data analysis for this, I knew it
Using traditionally available data on a
largely post facto basis to solve known
problems and opportunities
Collect and analyze all possible data in
real time to take decisions in real time to
solve problems and realize opportunities
9. You are doing your data right now
You are Scenarios How did you do data analysis
A takeaway 1. A surge at 4 pm every day
2. Low sales of 3 items every
alternate day
1. Your boys told you, You saw it
when you were there, you
say the hourly billing data
2. No idea
A retailer 1. End of month sales is
declining
2. Per user basket size reducing
on a day to day basis
1. No Idea
2. ERP or Billing software or BI
Hospital 1. Nurse retention ratio is down
2. Department patients billing
down
1. No Idea
2. Doctor changed, new
hospital, from the daily
patient report
10. Can we start by ourselves
10
Math and OR
Expertise
Develop analytic algorithms
Visualization Expertise
Interpret data to present in
meaningful ways
Tools and Users
Reduce complexity by
using off the shelf tools,
work with expert users
Vertical /
Domain Expertise
Develop hypothesis,
identify business issues,
ask the right questions
Data Experts
Data architecture,
management,
governance, policy
Use data for decision
making
Apply information to solve
business issues
yes Take help Later
11. how to start: do what you have: LHF
Set up a Cross
Functional Team
Do a Data
Inventory
Validate Data for
analytics use
Problems to Data
mapping
1. Get functional
heads, send out a
mail to all, go
online, IA and
Business analyst
2. Throw in some
contrarians and a
professor
3. Give mandate of
using data and
generating
shocks
1. Start with each
Functional head
2. Get data source
and sample data
for each function
3. Ask IT to do an
inventory of data
sources not
being used or
owned
4. Already owned
external
databases
1. Select tools to
use: Excel and
Access, Ask IT for
statistical
modeling tools,
Go online,
Kaggle, Watson,
Own App tools,
Google
2. Check Volume,
Velocity, Variety
to qualify data
1. For each data
source check
what problem
might it give an
answer to
2. Get a list of
problems, pet
theories, black
holes from the
CFT and @All
mail
3. Map them to the
data source if
possible and
make Tool choice
12. how to start: do what you have: LHF
Generate Analytics Course Correction Feedback loop Start over
1. Use tool selected
and run the
analytics
2. Check if the
results can be
viewed as
Diagnostic
analytics
1. Makes changes
to process, staff,
resources,
infrastructure,
design to reflect
analytics results
1. Check results and
see if there are
positives.
2. Check analytic
design , check if
you are
comparing
apples to apples
1. Do it all over
again.
2. Add more and
more data to the
mix, draw new
correlations,
more real time
data, more
behavioral data
Once you have tasted the LHF….you probably
would have made more money, understand data
better: Time to invest in tools and staff
13. Data Inventory Example
Functions Sources Sources Sources
Sales CRM Billing Software After Sales
Service/Mfg ERP / PPC Quality system Machine data
Supply Chain Accounting DB Logistics Sys
HR Attendance Payroll Social Media
HRIS
Marketing Social Media
Measurement
tools
Google Analytics Twitter Analytics
Finance Accounting SW Bank Data
Back
14. Running a Sales analytic
Sales
Decline
Qty
Per user
Fewer /
Diff Prod
Fewer
Users
Fewer/
User
Price
Per
product
Discount
Margin
Product
Mix
Correlations
• Higher Price
• New Products
• New store
• Cust Complaint
• Sales Returns
Trend Analysis and Forecasting
accuracy
• User behavior over different
time periods, Day, Month,
Season, Year
Unstructured data mining
• Social Media mention
• Email campaign reception
Correlations
• Discount
• Margin
• Product Mix
Trend Analysis and Forecasting
accuracy
• User reaction to price and
Supplier behavior over
different time periods, Day,
Month, Season, Year
Unstructured data mining
• Social Media mention of price
• Email campaign reception
Back
15. SME’s, Big Data and Analytics
Doing it
Some Case studies and Tools
Who are we
Canada Post analytics
showed that the risk of
dog bites is higher with
home delivery compared
to community boxes
16. Some places to start: Sales
P / O P / O
Who is our most valuable customer Who doesn’t pay by time but still gets a
good deal
Who is the least value customer Who does most sales returns, which
product does most sales returns
Lost sales, missed sales leads, high
probability sales leads botched
Which sales agent leads to most sales
returns
Customers who don’t come back, who
are they, where are they from, was there
a warning sign: fewer visits, lower billing
What happens after a customer does a
sales return, a complaint,
Is sales responding to Social Media
mentions
Which area is showing decline in sales,
which is growing,
Is discount working to increase my sales,
which promotion lead to a secular
increase in demand, is there a particular
time at which discounts work, is there a
particular product on which it works
Which products seem to be price
inelastic, is there a good time to increase
prices, do other goods get impacted if
price increases [cannibalization]
17. theory of inventive problem solving
• Wolfram Alpha, an online personal analytics tool that helps people analyze their Facebook feeds and
displays their account activity in pie charts, graphs and maps. Wolfram Alpha will expand its personal
analytics tools to allow users to input and analyze a wide range of personal data including emails,
instant messages, tweets and health data.
• Google’s Field Trip, a customizable local discovery engine. When people approach something
interesting, it automatically informs them about the location. No click is required and it can even read
the information to them. Field Trip bases its recommendations on user inputs and lets users find the
cool, hidden and unique things and places wherever they are
• ValuTex, a mobile marketing service, which sends special offers to smartphones of shoppers who have
opted-in when they enter a “geo-fence,” . These offers can be customized to specific customers using
profiles maintained by the merchant
• Global hotel chains are exploring applications that, with guests’ permission, recognize them via their
cell phones when they pull into the parking lot. These apps let hotels automatically check in guests
and have their room key and paperwork – and perhaps their favorite beverage – waiting at the front
desk before they even walk through the door
• Scout Mob and Womply, which allow local merchants to personalize offerings for particular
consumers, increasing customer loyalty. These services let local merchants combine information on
purchases with social media data to provide a more complete picture of customer preferences
• QuickBooks Online, includes a Trends feature that anonymously aggregates customer data and allows
small businesses to see how their income and expenses stack up against similar businesses. A roofer in
Philadelphia grossing $250,000 annually can compare results with other roofers in the area or across
the country.
18. theory of inventive problem solving
• A company wanted to shift its operations from City A to City B. Most employees won’t tell you if they
don’t like the move and wait till they get another job and then leave you. That would mean business
disruption. We made an analytic by going through employee data to come up with a profile that would
be most likely to quit, a profile that might not quit if some parameters were taken care of.
• Mackenzie Hospital: 34 beds, partnership between Cisco, Blackberry, Thoughtwire and funded by
Ontario CoE that picks up data from the workflow and tries to solve the problem of locating people and
getting to them the right information.
• EagleView Technologies provides roofers and solar panel installers with precise measurements of roof
sizes and slopes based on aerial photographs. Local contractors use the images and measurements to
inspect roofs, estimate costs and identify potential customers without the need for costly site visits
• When they didn’t have loyalty-card data, small businesses were dominated by their owner-managers,
who made decisions on their past experiences and any consumer information they could get their hands
on. One firm, was asked by a retailer to produce a range of ready meals, simply looked at other products
on the market and tried to imitate them.
• a large bank wants to monitor Twitter and Facebook for entries mentioning life-changing events. The
theory is that postings about developments such as pregnancies, births, or marriages can become
marketing opportunities for the bank. But the bank also wants to understand whether negative
developments, such as announcements about an acrimonious divorce, will raise a flag that credit lines
need to be carefully monitored or frozen
19. theory of inventive problem solving
• Financial Engines, helps hundreds of thousands of people navigate the complexities of retirement
planning. Founded by Nobel prize-winning economist Bill Sharpe, the firm provides individuals with
sophisticated financial advice – previously available only to the world’s largest institutional investors.
Its foundation is cloud technologies, new ways to access large financial data sets and advanced data
analysis tools.
• Parchment, a startup that helps high school students choose and apply to college. By analyzing a large
database of student profiles such as grade point averages, SAT scores and acceptance data, Parchment
assesses a student’s likelihood of admission to a specific school. It then determines what the student
must do to improve acceptance chances. Parchment also plays matchmaker, pointing students toward
schools that match their profiles, helping them find a good fit.
• Factual, which offers a cloud-accessible database of 58 million businesses and places of interest in 50
countries, effectively creating an uber Yellow Pages with a truly global reach. Businesses will be able
to use this data to identify, target and market to business customers anywhere in the world as easily
as to those in their home towns.
• Startup Compass, which collects data from tens of thousands of startups and creates best practice
information, benchmarks and performance indicators that help entrepreneurs make better decisions.
This new, cloud-based service currently has 17,000 companies submitting data and using it to help run
their businesses. .
20. Resources and Tools
• IBM's Watson Analytics advanced and predictive business analytics doesn't require using complex data
mining and analysis systems, but automates the process instead. This self-service analytics solution
natural language" technology helps businesses identify problems, recognize patterns and gain
meaningful insights: free and freemium.
• Google Analytics, Free Web-traffic-monitoring tool, provides data about website visitors, using a
multitude of metrics and traffic sources. where traffic is coming from, how audiences engage and how
long visitors stay on a website (known as bounce rates)
• InsightSquared connects to popular business solutions — such as Salesforce, QuickBooks, ShoreTel Sky,
Zendesk : Use for pipeline forecasting, lead generation and tracking, profitability analysis, and activity
monitoring. It can also help businesses discover trends, strengths and weaknesses, sales team wins and
losses from CRM. 99USD pm.
• Canopy Labs, a customer analytics platform, uses customer behavior, sales trends and predictive
behavioral models to extract valuable information for future marketing campaigns and to help you
discover the most opportune product recommendations.
• Tranzlogic works with merchants and payment systems to extract and analyze proprietary data from
credit card purchases. This information can then be used to measure sales performance, evaluate
customers and customer segments, improve promotions and loyalty programs, launch more-effective
marketing campaigns. No tech smarts to get started — it is a turnkey program, meaning there is no
installation or programming required. Simply log in to access your merchant portal.
• SiSense, which allows small companies to draw information out of the transaction statistics being
collected on their e-commerce sites and in CRM databases Prism, is intended to be used by business
analyst (rather than IT experts) who are interested in running "self-serve analytics,“
• OneQube The program mines comments and conversations on social networks like Twitter to identify
the most relevant prospects, or Constant Contact offers big data-based benchmarks to help marketers
21. Resources and Tools
• ODX is a partnership between Communitech, the University of Waterloo, D2L
(Desire2Learn), CDMN (Canadian Digital Media Network), and OpenText; the initiative will
evolve over the next three years using FedDev Ontario’s Investing in Commercialization
Partnerships (ICP) grants for small business in Ontario, as well as non-profits and post-
secondary institutions. The Open Data Exchange (ODX) depends on the sharing,
distribution, and analysis of large datasets. The founding partners of ODX consist of for-
profit businesses, non-profits, and a post-secondary institution. The local community has
to sign up as a supplier of data to maximize the impact of ODX. Verticals: - Consumer
products; Education; Energy (Electricity/Oil and gas); Finance; Health care; and
Transportation
• 2001, the Government of Canada funded a not-for-profit corporation called Canada
Health Infoway. Its charge to facilitate health care transformation includes developing
health information standards, providing tools and services for technology vendors, and
working with the clinical community to enhance its value.
22. Resources and Tools
• Workforce Analytics Forum by the Canadianinstitute.com is a program developed
specifically for HR and workforce analytics professionals besides getting course credits
• Community Cloud: online collaboration and business process platform: Salesforce To
bring employees, customers, suppliers and distributors together. Targeted
Recommendations an addition to this, uses algorithms to analyze both structured and
unstructured data so the most relevant content is delivered to each community member.
All this is easy to do by using templates so you don’t need IT too much
• Twitter Analytics is an easy-to-use, free tool :For monthly account summaries, which
tweets generated largest engagement, identify top followers of your brand.
• Business analytics from Bell can help you in building an analytic engine and so also if you
are an Intuit Quickbook user. Intuit has collective data of more than 45 million customers
that ranges from individual purchases and spending habits to business inventories,
transactions, and trends. QuickBooks Online Trend’s goal is to help the mom and pop
store compete with Macy’s or Starbucks down the street.
• The Chang School offers several programs to provide proficiency and skills in big data and
advanced analytics. Professional Master's Program in Big Data at the SFU. Lassonde
School of Engineering will lead a program in Data Analytics and Visualization providing
interdisciplinary training in both computational analytics and perceptual design
methodologies
23. Points to Ponder
Data is the new Oil. Data is just like crude. It’s valuable, but if
unrefined it cannot really be used.
– Clive Humby, DunnHumby
We have for the first time an economy based on a key resource
[Information] that is not only renewable, but self-generating. Running out
of it is not a problem, but drowning in it or squandering it is.
– John Naisbitt
24. SME’s, Big Data and Analytics
Doing it
Some Case studies and Tools
Who are we
26. Leadership Leadership Leadership
Sales & Ops Sales & Ops
Virtual
Organization
Virtual Leadership
Support team
Sales & Ops
Support team
Consulting
Support
Start up /
Turnaround
Emerging /
Languishing
Mid sized / Large
Client Ubika
However SME’s normally have skills only in one or two functions which makes our integrated
multi-disciplinary approach the right fit for SME’s that want to hit the ground running
Solving problems / realizing opportunities almost
always require skills in multiple functions.
What do we do
27. Who are we
USA and Process Consulting
Maria Achilleoudes has a MSc from Columbia University and a BSc from
City University of New York and a Lean Six Sigma Master Black Belt . She
first worked with IBM’s Quality, then Marketing Division in New York. She
then joined Universal Bank, Cyprus before starting a consulting firm which
works on Cost reduction and Process Improvement jobs.
Canada and Strategy
George Antony has spent 60% of his time with the Big 4 in advisory and the
rest in the Industry heading finance for a start up where he raised equity
and debt, set up the finance department and managed procurement. In the
Big 4 he advised a variety of clients on Process improvement and strategy.
At Ubika he works with clients on Strategy, Training and Interim
Management. He also teaches entrepreneurship to rural entrepreneurs
george@ubika-hetu.com | +1 647 771 2017 | @togeorge