deloitte italy analytics experience bootcamp€¦ · analytics needs broken down at capability...
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Deloitte ItalyAnalytics Experience Bootcamp
IDO 2019 Italian Survey
Results Summary
Alfredo Maria Garibaldi, 02.04.2019
IDOs see analytics as a core capability to tackle complex business problems and to address the growing analytical trends
ANALYTICS
They do not view Analytics as a project with a start and end date but as a continuous improving process
ALWAYS
IDO - Insight Driven Organization
An Insight Drive Organization is one which embeds analysis, data and reasoning into its decision making processes
IDO Maturity Curve
Based on Deloitte’s global IDO Model methodology, an organization can assess itself against the Insights Maturity Curve which has 5 key stages
Aware of
analytics, but little
to non
infrastructure and
poorly defined
analytics strategy.
Adopting
analytics, building
capability and
articulating an
analytics strategy
in silos.
Expanding ad-
hoc analytical
capabilities
beyond silos and
into mainstream
business
functions.
Industrializing
analytics to
aggregate and
combine data from
broad sources into
meaningful content.
Transforming
analytics to
streamline across
all business
functions.
Stage 1
Analytically
Impaired
Stage 2
Localised
Analytics
Stage 3
Analytical
Aspirations
Stage 4
Analytical
Companies
Stage 5
Insight Driven
Organization
Data Driven
Insight Driven
For the first time in Italy
Conducted online between January and February 2019, it was directed to C-Levels across a wide spread of industries and organization sizes.
We proposed 45 questions, mainly grouped in 5 analysis dimensions: Strategy, People, Process, Data and Technology.
With this survey we tried to understand how much Italian companies are embedding analysis, data and reasoning into their decision making processes.
#Benchmarking your analytics journey
2019 IDO Maturity Survey
34% of Italian companies consider themselves in the Stage 4 - ‘Analytical Companies’ of the IDO Maturity Curve, but no company seems evaluating itself as an Insight Driven Organization.
A business-driven analytics strategy to map your journey
0 5 10 15 20 25 30 35 40 45
Stage 1 - Analytically Impaired
Stage 2 - Localised Analytics
Stage 3 - Analytical Aspirations
Stage 4 - Analytical Companies
Stage 5 - Insight Driven Organisation
% ITA 2019 % UK 2018
The following chart illustrates how companies have self-assessed with regard to the IDO Maturity Curve in 2019 in Italy and in 2018 in the UK
Only 5% of our respondents has a Chief Data Officer or a Chief Analytics Officer, but the most relevant point is that we found “Analytics are endorsed informally across the organization”.
The Ownership Debate
0 5 10 15 20 25 30 35 40 45
Analytics informally championed in organisation
Visible and active analytics leadership at functional level(business unit/group)
C-suite or senior leadership champion analytics without aformal mandate
C-suite member has formal mandate to drive analytics acrosstechnology, people, process, data and strategy
Chief Data sits on the executive committee, ensures thatanalytics is driven using people, processes, technology, data
and strategy lens
% ITA 2019 % UK 2018
C-Suite Leadership - Which of the following statements best describes who supports Analytics at the board table and guides organizational changes?
Analytics talents have a combination of technical skills, analytical skills, storytelling and data visualization skills. These kinds of profiles are hard to find, and companies face hard challenges to cover the needs in analytics fields.
People are the main resource
Talent - All cross-industry responses to the question, “What statement best describes how analytics is embedded in the talent life cycle?”
19%
38%
28%
10%
5%
0% 5% 10% 15% 20% 25% 30% 35% 40%
Analytics needs are not taken into consideration for hiring
Analytics needs defined and considered for hiring/developingspecific roles
Analytics needs are defined and influence hiring and talentdevelopment strategies for all roles
Analytics needs broken down at capability level and embeddedinto hiring and talent development strategies and processes
An analytics mindset seen as essential from the board room tothe front office and processes exist to hire or develop teams
Purple People
Technic
al skills
Data
analy
sis
Busin
ess a
cum
en
Sto
ryte
lling
Understanding how technology
can be leveraged to solve
business problems.
Evaluating data using analytical and
logical reasoning for the discovery of
insight, e.g. predictive modelling.
Understanding of the company’s
business strategy, current issues,
priorities and industry trends.
Articulation of insight to explain
current and forecasted trends,
their impact and opportunities.
Communication and interpersonal
skills are necessary to articulate
insight gained from analysis.
Purple People
Data Analysis
Technology Alignment
Macro-Perspective
Business knowledge
Business Commentary
Soft Skills
Defining, developing, and
implementing quality assurance
practices and procedures for technical
solutions and validating hypothesis.
Testing & Validation
SQL querying
Data Modelling
Understanding of the underlying
theory and application of key
reporting software.
Reporting Software
TECHNICAL & ANALYTICAL
BUSINESS & COMMUNICATION
Building a dedicated team with the right balance of technical skills (red skills) and industry knowledge / business acumen (blue skills) is crucial for the success of a specialised Insights program. We define this new valuable blend as Purple People.
Querying and manipulating data
to facilitate the solving of more
complex problems.
Understanding of the main key
performance indicators and
business related context.
Structuring data to enable the
analysis of information both internal
and external to the business.
48% of the total respondents do not have a centralised structure to share details of the previous analytical activities across the firm.
Knowledge Management
Knowledge Management - All-cross industry responses to, “How do you leverage the knowledge and skills you develop as you become more analytical?”
48%
19%
19%
5%
9%
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
No centralised location with documentation of previous analyticalendeavors
Centralised location with documentation of some previous analyticalendeavors but not fully accessible
Centralised location with documentation of some previous analyticalendeavors, accessible to all
Centralised location with standard, guidelines, documentation ofprevious analytical endeavors is made aware of and accessible to all.
Conferences and events are organised to share the best practiceswithin the business line
Centralised classified repository with standards, guidelines, goodpractice, documentation of all analytical endeavors accessible to all
within the enterprise. Frequent enterprise-wideconferences/networking events organised
We tried to understand where companies find the biggest barriers in the usage of analytics. The most common answer (almost 62%) is “Embedding analytics into processes”.
Process is the main barrier
All-cross industry responses to “in which phase of the analytics process is your organization more exposed to challenges?”
50%
40%
35%
2%
30%
20%
62%
15%
20%
2%
0% 10% 20% 30% 40% 50% 60%
Understanding analytics
Managing your data
Implementing analytics
Delivering information
Using cognitive technology
Communicating value
Embedding analytics into processes
Optimising insights
Measuring the output of analytics
None of the above
Which of the following statements best describes how your analytics governance structure is defined?
Most of respondents - 62% - told us that rather than having a process and a formal structure, governance is currently achieved through a few individuals or teams working together.
Know your Data
29%
33%
14%
10%
14%
Rather than having a process and a formal structure, governanceis currently achieved through some key individuals working
together
Rather than having a process and a formal structure, governanceis currently achieved through a few teams working together
There is a well-defined governance structure in your organization
There is a well-defined governance structure and process to allowanyone within a group or a business line to ask questions of datagovernance so that they are tracked and if necessary investigated
There is a well-defined governance structure and a process toallow anyone within the organization to raise issues of data
governance so that they are tracked and if necessary investigated
0% 5% 10% 15% 20% 25% 30% 35%
Which of the following statements best describes how your organization relies on Data Quality and Data completeness and monitor them?
Improvements are necessary to define Data ownership and stewardship roles - 24% of respondents indicated that these roles are not yet defined – although, Data quality processes are standardized for a good 19% of our respondents.
Data Quality as an asset
24%
33%
14%
10%
19%
Data ownership and stewardship roles not yet defined
Data quality issues addressed in a reactive mode
Data quality measured and proactively monitored
Data ownership and stewardship roles clearly defined andassigned
Data quality technologies and processes standardisedcross-enterprise
0% 5% 10% 15% 20% 25% 30% 35%
What kind of vendor ecosystems supports your analytic programme?
The survey’s answers highlight companies understanding that designing a cross-project enterprise architecture is a proactive goal. However, only 19% recognize the reference architecture as an enterprise standard for all data-related projects.
Towards an advanced Technological
Framework
5%
4%
34%
38%
19%
0% 5% 10% 15% 20% 25% 30% 35% 40%
There is no reference architecture
The reference architecture is under development
The reference architecture is considered by some businessunits for their process and data requirements
The reference architecture is considered by the keybusiness units for their process and data requirements
Within the enterprise, the reference architecture isrecognized as a standard for all data-related projects
To become an IDO, companies must implement a successful Analytics Strategy, by developing one coherent vision and a comprehensive tactical implementation plan.
Actionable Advice
1. Assessment
Analysis of current analytics
capabilities and identification of
a list of challenges and
opportunities to focus on moving
forwards
2. Design
Creating a long term strategy
and vision for analytics, the
services and capabilities required
and the design the structure of
the operating model
3. Roadmap
Planning the programme and
change process, including
prioritization and dependencies
between business and
technology aspects
Stakeholder engagement including education and training, workshops and IDO Labs
• Conduct an IDO Capabilities
Assessment and create a heat-
map to understand existing
capabilities and ensure a holistic
view of organizational
requirements
• Identify top analytics priorities
including improving existing
execution and brainstorming
pressing ‘Crunchy Questions’ the
business would like to explore
• Alignment against and analytics vision, formulation of an analytics strategy and education of senior stakeholders to ensure buy-in
• Development of a business case including immediate investment needs and expected quick-wins
• Definition of a target operating model provides a foundation for the journey
• IDO prioritization to reduce a long list of opportunities to a selection of prioritized and manageable strategic and tactical projects
• Transition states between current and future state are defined as programme phases
• Roadmap is based on agile methodology and adapts as the organization matures along the IDO journey
15
Thank you.
Alfredo Maria GaribaldiPartner – Analytics Country leader [email protected]
Giuseppe TarantoDirector – Lead IDO [email protected]
Data Will Rock YouE x p e r i e n c e A n a l y t i c s B o o t c a m p
Stefano MagniManager -Member of IDO Leadership [email protected]