The document summarizes an upcoming two-day workshop on using big data to drive business decisions for revenue and profitability. The workshop will cover topics like key performance indicators, customer segmentation, retention management, and using data to measure marketing effectiveness. Experts from companies like Civitta, Uber, and Vinted will share their knowledge of applying analytics in industries like telecommunications, transportation, and e-commerce. Attendees will learn practical techniques and work on cases and exercises to develop action plans for implementing data-driven strategies in their own organizations.

1. EXPERTISE. ACT.
Three stone cutters were asked about their jobs.
The first one replied, “I’ m paid to cut stones”.
The second replied, “I use special techniques to shape
stones in an exceptional way, here let me show you”.
He proceeded to demonstrate.The third just smiled and said,
“I BUILD CATHEDRALS”.
JUNE 6-7, 2016
DATA DRIVEN
DECISIONS FOR
PROFITABILITY
Most important
KPIs setup for
revenue and
profitability
Identification
BIG DATA
benefits in my
organisation /
my functions
Data driven tools
towards
sales and
profitability
improvement
BOOST
BIG DATA
control

2. In the computerized world of nowadays every company piles up huge amounts of various
customer and process related data. However, the value is not in the amount of data
organization has, but what it does with that. “Industrial Insights Report for 2015 by GE and
Accenture” indicates that 53% of Top Performing companies make data-driven decisions
very frequently.
Program Intro: Opportunities & Challenges
The use of Big Data is becoming a key basis of competition and growth for individual firms.
In most industries, established competitors and new entrants alike will leverage data-driven
strategies to innovate, compete, and capture value from deep and up-to-real-time
information. These days examples of such use of data is in every sector: Retail – Walgreens;
Airlines - Delta; Media - FT.com; Logistics - UPS; Financial Services – AIG, e-commerce -
Amazon. These successful examples includes automated individualized proposals for
Amazon visitors based on their past purchase or search history or fleet optimization by UPS
that already saved from driving 364 million miles and over 39 million gallons of fuel since
project reliese.
”Industrial Insights Report for 2015” found that:
- 89% of respondents who have implemented at least one big data project already see it as a
way to revolutionize business operations
- 84% of those surveyed believes big data analytics will “shi the competitive landscape for
my industry” within a year and 87% believe so in three years
- 89% believes a lack of big data adoption will create a risk of losing market share
State of the art mathematical data mining leeds to sophisticated customer segmentation,
churn prediction, system fault prediction and other methods that heavily influence financial
performance figures of each Company . 90% of standart Organisations revenue and profit
growth is usually achieved through improving product and service porfolio and by
streamlining the internal processes – Data Driven decisions is one of the crussials point
there.

3. TAKE THE
NEXT STEP
www.executive.ktu.edu/big-data
REGISTRATION:
PRICE
799 EUR
PLACE
AMBERTON hotel
L. Stuokos-Gucevičiaus g. 1
Vilnius
TIME
June 6-7, 2016
LANGUAGE
English / Lithuanian
6-7 core KPIs geared towards sales improvement and their application explained in
detail with hands-on experience delivered;
Program Values / Main take-a-ways:
A good feel what big data actually means and what it takes to implement it;
Principles of data-driven decision making process oriented at revenue enhancement;
WHO SHOULD ATTEND
Positions: CEOs, CFOs, Head’s of Commercial dep., Marketing dep., Sales dep
Companies types: Medium and Large size
Industries: Retail, E-Commerce, Services: Finance / Insurance / Logistics /
Accommodation / Travel / Healthcare / Utilities
Best practices with different revenue management techniques;
Best practices on measuring and managing customer loyalty;
Solutions and tools geared towards getting the most of your marketing investments;
Data Driven techniques for:
- measuring customers value and rights KPI’s in : pricing decisions, marketing solutions;
process management;
- building data based patterns - customer base segments, customer behaviours, forms
of churn, root causes for bottom line costs and etc.;
- making more precisely tailored products and services;
- improving the development of the next generation of products and services,
Principles and solutions for starting analysing the big data companies already hoarded.

4. EXPERTISE.
ACT.
DAY 1
Introduction: Understanding Big Data in Business
Data-driven decision making:
Data culture at the organisation: data availability, reliability,
openness.
When does the data help you make better decisions and when do
you still need to trust your gut feeling?
Data-driven decision process and corporate politics: not an easy
couple.
Effective application of KPI’s
Limits of data: in the end, you still need to talk to your clients.
KPI application in business processes: Important insights we get by
analysing information in a structured way.
Overview of the most important KPIs for revenue and profitability
control.
Revenue management techniques
Data analysis on a customer level: Basic approach, why this can be
important
Practical questions around data
Customer segmentation: overall idea
PROGRAM OUTLINE
Ways to create value through data: revenue and profitability effects.
The next step: big data and real time automated decision making.
Customer value and behaviour analysis by customer segments
Business cases / Practical workshop / Practical exercises
During the workshop a take-away task will be given to participants. The solutions will be discussed the next day.
Retention management
The definition and interpretation of Churn. Why and where is it
important?
Analyzing the reasons for churn
Churn calculation and monitoring techniques
Evaluation of your sales & marketing efforts
Campaigns: possible goals and types
Being smart in what you do with marketing experiments
Measuring effectiveness of a marketing campaign
Program Resume: developing concrete Action Plan
DAY 2
Who intends to leave us? Churn prediction models
Retention strategies
Practical cases and workshop
Bringing revenue and churn together: the concept of customer
lifetime value (CLV)
Practical cases and workshop
Business cases / Practical workshop / Practical exercises.

5. EXPERTISE.
ACT.
OUR EXPERTS TO TAKE A CHALLENGE
Justė Pačkauskaitė,
Partner at UAB Civitta
Competences: 10 years of experience in Finance, Strategy, Data analytics and
Sales&Marketing. Justė is responsible for analytics and research project stream in Civitta.
Justė has mainly worked in such industries as Telecommunications, B2B Professional
services, Insurance, Real Estate management both in Lithuania and abroad. Justė holds
CFA level III certification.
Impact: practical knowledge of data analytics based sales and marketing strategy
formulation; financial analysis, KPI based budgeting, cost control, investment control,
managerial reporting.
Enn Metsar
General manager at Uber Technologies Estonia
Enn is a US educated executive with extensive prior experience in investment
management and business development. He has over ten years of experience in
managing equity funds, technology driven venture capital, management consulting,
trading, business development, sales and investor relations from both sides of the
Atlantic. Enn holds an MSc degree from Carnegie Mellon University.
Mārtiņš Bajārs,
Associate partner at SIA Civitta Latvija
Competences: 9 years of international experience with focus on customer analytics and
telecommunications. Specific areas of expertise: Strategic Analysis, Pricing Optimization,
Product Portfolio Optimization, Customer Retention & Churn Management, Customer
Segmentation, Financial Analysis.
Impact: real life near-time data analytics tool creation and application in European and
African mobile network operators.
Competences: 10 years of experience in finance, asset management and data analytics.
Petras has worked with large sets of data (Vinted - 10 million users). His experience at
finance comes from managing pension and investment funds as well as overseeing
private equity projects at Invalda group.
Impact: practical knowledge of data analytics, data infrastructure, business modeling,
data driven decisions and leading the analyst teams to provide data insights.
Petras Kudaras
Data and business analyst
Vinted - is a peer-to-peer marketplace to sell, buy and swap clothes / the highest-valued
startup in the Baltics, 2014 - €80 million/ operating in11 countries.
Multinational online transportation network company providing service in 58 countries
and 300 cities worldwide. Ranked us 48th-most powerful company in America with
estimated worth of 62.5 billion $.
Company’s business model is largely based on Big Data principle. By using them in
very effective way Uber has disrupted whole Taxi Industry and become worldwide
phenomenal organization.

6. KTU Executive School: www.executive.ktu.edu
For more information, or to apply please contact:
Eva Sabaliauskaitė
Business Development and Sales Director
+370 699 95 779
eva.sabaliauskaite@ktu.lt