Final submission of team Data Insights

1. nickelring corp.
OAP Final Submission
Team Data Insights
20 May 2012
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2. Executive Summary
Background
• nickelring is a firm committed to the vision of developing a meaningful data analytics solution for SME’s
• A team of 11 motivated individuals (originally 14) from 7 countries have worked extensively over the last 3 weeks to
develop a compelling proposition that addresses a “real-need” of the target client
Initial hypothesis
• There is a gap in the market – The data analytics needs of SME’s around the world are significantly underserved
• There is a market in the gap – This represents a large enough market for a sustainable commercial venture
Key milestones achieved during the first three weeks
• Market sizing – There is sufficient evidence that Data Analytics is a large, growing business and that our addressable
market (SME’s) is of significant size (this is not a niche play) that is currently under-served
• Market testing – The feedback (through survey & interviews) validated our hypotheses that current systems are not “easy
to use”, with average satisfaction levels among users and highlighted interesting aspects that will need us to pivot
• Competitor analysis – While there are a number of players in this space, there is a lack of a genuine focus on the needs of
the SME’s with products offering little differentiation and with low perceived value
• Value proposition – At nickelring (www.nickelring.com) we intend to develop a unique product for the SME’s that will
differentiate on three aspects – The user experience (“Ease of use” to be specific), time to market (decision making &
relevance) & market leading ROI (balancing the price-value equation)
We will pursue this initiative into the OEP phase
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3. Our process
Opportunity Analysis Project Opportunity Execution
Phases
Project
Proposition Development Proposition Testing
Key tasks  Team formation – Assignment of  Finalise proposition – clearly  Develop prototype
roles & responsibilities articulate points of  Develop service proposition
 Agree on communication tools differentiation
 Develop marketing strategy
 Develop questionnaire & deploy  Market test proposition through
 Develop distribution strategy
Survey & face-to-face interviews
 Develop functional website  Develop financial model
 Pivot and refine proposition
 Educate “diverse” team on  Outline operational risks and
fundamentals of “Data Analytics”  Develop business model canvas
mitigation plan
 Conduct competitor analysis  Outline market level risks &
mitigation plan
 Develop high level market sizing
Outcomes  Initial feedback from potential  Finalised value proposition  Prototype
customers  Results from market testing  Cost benefit analysis
 Market sizing  Execution plan
12 May 19 May
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4. Why SME’s?
• Empirical research has highlighted that SME's currently have 4 critical technology needs
1. An accounting package
2. An email system
3. A website
4. A set of productivity tools (Excel, Word, etc.,)
• It is our hypothesis is that there is a fifth need and that is around the need to better understand their data -
predominantly financial and customer/sales data
• The systems that are currently on offer are
– Too technical to implement
– Reasonably expensive
– Difficult to change and are quite static
– Unable to handle multiple, unstructured data sources in an easy to use manner
– Not intuitive
• However, technology has now advanced such that cloud based solutions delivered in SaaS/PaaS format make
it affordable to develop a meaningful solution for SME's.
• Most software firms aim to service the large enterprise- there is a big gap in the SME space
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5. Selected survey results (N=25)
Extensive focus on
sales &
forecasting –
revenue
generation
avenues
Cost of tool is
important, but
A startling response-
interviews
set with 85% scoring
confirm not
3 or below
necessarily
“cheap”
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6. Summary of interview feedback
• The team conducted 15 interviews in total with a range of firms in Singapore, USA, South Africa, India, Italy,
etc.,
• Sectors were varied (as our proposition is vertical agnostic) – Law firm, Chemical manufacturer, Supply Chain
management product developer, Government R&D, IT hardware solutions, etc.,
• Key learning:
– Ease of use is the single most important factor emerging as a client need
– Price is not the most important consideration: Customers are willing to pay for a good quality product,
i.e., this is not a commoditized market
– Data availability and accuracy is a major concern: While the overall concept was well received,
significant concerns were raised on this point and we were requested to try and develop something
that could potentially address this basic issue.
– Response time and security (data privacy) were raised as key concerns for cloud based solution
– Some respondents were unaware of appropriate BI tools and/or did not believe they needed one
– Excel is the primary substitute at most firms for data analysis
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7. Hypothesised market size*
Total number for firms in
Tier 1 the world - ~ 500 million
Total number of SME’s in the world
• ~90% of registered firms are SME’s
Tier 2 • ~450 million SME’s globally
SME’s who are active & material - ~ 90 mil
• There are ~20% are inactive SME’s and
Tier 3 40% are “mom & pop shops”
Target Market Analysis
• ~20% are sizeable firms with no critical need for Data
Analytics (DA) / Business Intelligence (BI) tool
nickelring • ~25% are estimated to have an existing solution
target • Profile of target client
market • Revenue p.a.: USD 1 mil +
• Number of employees: 10 – 250
• Target market for nickelring – ~50 million firms
Our proposition is global in nature with a large target market!
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Source: Based on nickelring research and estimates
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8. Industry analysis highlights that this is an attractive market
Barriers to entry
Threat of new entrants
• This is a very lucrative market globally
with strong growth forecast (>15% pa
over the next 5 years) & will attract a
number of new entrants
• However, effective execution and
access to distribution channels is a
challenge
• Strength of threat: High
Supplier power
Supplier power Industry rivalry
Industry rivalry Buyer power
Buyer power
• Technology is continually maturing & • A fragmented market with – large • Typical SME management team will
hence there is a need to constantly adapt global players & niche / boutique firms have limited technology and/or
analytical resources
• Recruiting resources (especially for • Large players dominate big corporates
startup) is a challenge space but are weak in SME’s • SME’s will appreciate simple product
with good service at affordable price
• Funding will be a constraint, but not a • Niche firms lack scale & differentiation
point
show-stopper for unique proposition
• SME market under-served
• Strength of threat: Low
• Strength of threat: Medium
• Strength of threat: Low
Substitutes
• Limited substitutes to BI/DA tools for an
organisation to glean insights
• Excel is perhaps the most popular tool,
especially in the SME space
• Strength of threat: Low
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9. Competitor analysis
Competitive landscape1 Large players that service
big enterprises; Leverage
other products; Not suited
for SME’s (despite promise)
2
Basically reporting /
dashboard systems;
Low level
differentiation; highly
fragmented
• Trad. Players represent the larger firms &
“Open” represents smaller firms
• Analysis will enable nickelring pricing
Source: 1)Source: Lowering the Cost of Business Intelligence With Open Source
2) nickelring analysis based on competitor pricing information
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10. nickelring – Value proposition
Strategy Canvas*
High
Capability
Low
Value Attributes
By providing advanced analytics and choice for efficient deployment,
nickelring aims to democratize the use of analytics
Concept: Blue Ocean Strategy
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11. Risks and mitigations
Based on the analysis* of 32 startups that failed, the following were the top 5 risks that were identified for
new ventures. Here is how we plan to mitigate the risk
Key Risks Mitigating activities
Ignore customers • Deploying our survey to over 300 SME’s globally
• Conduct at least 25 face-to-face interviews with target customers
• Build relationships with 5-10 clients to test proposition on an ongoing basis
No market need • Our research and credible market reports (by IDC, Gartner, IBM) clearly indicate that:
– There is a need for data analytics globally and this is a growing market
– SME market is significantly under-served
– The market is large and profitable
Not the right team • We have a built a balanced team that consists of motivated individuals that are representative
of key organisational functions (Product, Technology, Marketing, Finance, Operations, etc.,)
• During the first two weeks the team members have displayed an affinity to high performance
and those who could not contribute found themselves self-selecting out of the team
Poor marketing • We are working on our marketing strategy in conjunction with product development
• The emphasis of the message will be on key value attributes – Simple, Secure & Easy to use
Need business model • We have a good grasp of our business model (that is being fine tuned) – Both in terms of
solution delivery and the economics of operations
• We will elaborate on this during the OEP presentation
Source: http://www.chubbybrain.com/blog/top-reasons-startups-fail-analyzing-startup-failure-post-mortem/
Note: We excluded “Ran out of cash”, which was the 5th reason, as it is not yet applicable for us.
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12. Next steps
• Commence work on OEP
– Finalise proposition including product features
– Develop technical architecture
– Develop product prototype
– Engage alpha & beta testing clients
– Develop marketing strategy
– Evaluate and build distribution partnerships
– Develop financial business case
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13. Appendix
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14. Team composition
Name Location Work experience Core competence Education
Alessandro Dublin 2 Years Software Engineering (C++, VHDL) BSc, MSc
Arnaud Tahiti, French 13 Years Marketing & Business development BSc, MSc
Polynesia
Bharath Singapore 2 Years Software Engineering, Database BSc Eng.
Administration
Deepak Singapore 8 Years Software Engineering, Machine Learning BSc, MSc, MTec
Techniques
Filip Antwerp Area, 10 Years Business Consultancy BSc Eng.
Belgium
Matej Slovenia, EU 10 Years Software Engineering, System Administrator BSc. Math
Munir NC, USA 15 Years PLM, Business Analytics (Data Mining) BSc. Eng , MBA
Patrick CA, USA 1 Year Software Engineering Reading BSc. Eng
Romil New Delhi, 10 Years Internet Marketing & Branding, E-commerce BSc (HM), MTM
India and Web development
Sajith Singapore 5 years Software Engineering, Data Mining, BSc (Hons) Eng.
Semantics
Sandeep Singapore 14 years Strategy Consulting Engineer & MBA
Business case development
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15. About nickelring
Why nickelring?
You can visit us at • Nickel is a chemical element with the chemical symbol
www.nickelring.com Ni and atomic number 28. It is a silvery-white lustrous
metal with a slight golden tinge (Source: Wikipedia).
What does that have to do with Data Analytics for SME,
you ask?
• The answer lies in the underlying characteristic of
Nickel. We all know that Nickel is an easily available
metal that was widely used in manufacturing… well a
nickel (US currency). However, did you know that
Nickel is also a key component of superalloys that are
used in the aerospace, industrial gas turbine and
marine turbine industry? Today, over 60% of the
global Nickel production is consumed in making nickel-
steels used as part of high-strength infrastructure.
Moreover, under appropriate treatment Nickel can
obtain the luster of silver.
• One simple metal – multiple benefits!
• Similarly, we are committed to developing a simple
solution that will provide you and your organization
with multiple benefits. We intend to indulge in a
virtuous cycle of listening to you and taking your
feedback onboard to develop insanely great products.
And hence the name – nickelring! 15
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16. Supporting data points – Data Analytics is a booming market (1/2)
More data required to support decisions – McKinsey 2011 Survey*
• Executives say their companies still rely upon a mix of data and experience in decision making, although
they are increasingly looking to analytics tools for support
• Despite the promise of big data to reshape strategy and decision making, more than 75 percent of
respondents to this survey report that their organizations’ greatest benefits from data use flow from clear
and timely reporting of financial and performance metrics
– Only about half say they seek to use data to provide new business insights or develop new
information-based products and services
• Respondents highlight three barriers to more effective use of data and analytics :
– A cultural preference for experience over data;
– A lack of skills in synthesizing and translating the analytics and data for decision makers and
– Concerns that the data quality is poor
Source: McKinsey & Co online survey conducted from October 4 to October 14, 2011, and generated responses from 927 executives.
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17. Supporting data points – Data Analytics is a booming market (2/2)
• Analytics is the application of computer technology, operational research, and statistics to solve problems in
business and industry*
• Analytics is a rapidly growing industry with a lot of existing and emerging players. According to IDC analytics
market will be $33.9 Billion in 2012 – growing at 8+% since 2011.
• Most of the advanced analytics market is currently owned by big players such as IBM, Oracle, SAS,
Microsoft, SAP, Microstrategy, etc.
• Most consumers of advanced analytics capabilities are medium-large size enterprises as these solutions are
resource-intensive in terms of hardware, software and licensing costs.
Excel still the predominant solution in finance – WesierMazars study of Global Insurance related firms 2011
• The WeiserMazars study found that 87% of the CFOs they surveyed relied heavily on Excel spreadsheets in
their financial close and also in their FP&A activities, as well as for budgeting and reporting.
Source: Wikipedia
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