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Team Data Insights - OAP submission 1.

Team Data Insights - OAP submission 1.

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nickelring - OAP submission 1 nickelring - OAP submission 1 Presentation Transcript

  • nickelring corp. OAP – Submission 1 Team Data Insights 12 May 2012 1 Confidential
  • Executive SummaryBackground• nickelring is a team dedicated to the common vision of developing a meaningful data analytics solution for SME’s• We have chosen to adopt a slightly different approach for the OAP, in that: – We have deployed the survey to understand the current situation at SME’s (their needs and constraints) – We are conducting a comprehensive competitor analysis to identify features being offered and gaps – We intend to use the field-interviews to test our specific propositionKey milestones achieved during the first two weeks• Based on our research, we are convinced that Data Analytics is a large, growing business and that our target market (SME’s) is of significant size (this is not a niche play) that is under-served• The survey feedback (to date) validates our hypotheses that current systems are not “easy to use”, there is only a average satisfaction with current systems and highlights interesting aspects that will need us to pivot• We understand that “not listening to customers” is the key reason for most start up failures; we are taking steps to ensure we listen and built our website (www.nickelring.com) clearly emphasizing this message to target clientsNext steps• We are working on our value proposition – it is a challenging task to find a middle ground between advanced data analytics and primitive reporting, which will drive the price point of our product 2 Confidential
  • Our process Opportunity Analysis Project Opportunity ExecutionPhases Project Proposition Development Proposition FinalisationKey tasks  Team formation – Assignment of  Finalise proposition  Develop prototype roles & responsibilities  Market test proposition with ~25  Develop service proposition  Agree on communication tools potential clients  Develop marketing strategy  Develop questionnaire & deploy  Pivot and refine proposition –  Develop distribution strategy  Develop functional website develop detailed product  Develop financial model features  Educate “diverse” team on  Outline operational risks and fundamentals of “Data Analytics”  Determine price range mitigation plan  Conduct competitor analysis  Outline market level risks & mitigation plan  Develop high level market sizingOutcomes  Initial feedback from potential  Finalised value proposition  Prototype customers  Results from market testing  Cost benefit analysis  Market sizing  Execution plan 12 May 19 May Our approach is slightly different. However, given the complexity of the task, we believed this to be the optimum approach 3 Confidential View slide
  • 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 – 500 mil • Number of employees: 10 – 250 • Target market for nickelring – ~50 million firmsOur proposition is global in nature with a large target market! 4 Source: Based on nickelring research and estimates Confidential View slide
  • 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 5 Confidential
  • 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 pricingSource: 1)Source: Lowering the Cost of Business Intelligence With Open Source2) nickelring analysis based on competitor pricing information 6 Confidential
  • Value proposition Strategy Canvas* High Capability Low Value Attributes By providing advanced analytics and choice for efficient deployment, nickelring wishes to democratize the use of analyticsConcept: Blue Ocean Strategy 7 Confidential
  • Selected Survey results (Venture Lab participants only; N=20) In which area do you or would you find the most What problems (if any) have you encountered with benefit from a data analytics tool? your current tool? Extensive focus Sales improvement on sales / Difficult to turn DA marketing data into a real solution Marketing Strategy Usability Operational Interpretation of data Technology Lack of Planning & customisation for forecasting different data Ease of use is the Finance Cost primary concern – Customer None costs come in last relationship If you are not using a BI/DA tool, it is because of Satisfaction rating of current tool being used (1 – poor and 5 – excellent) Reflects complexity in deploying current Lack of skill tools A startling response- set with no scoresNot aware of tools, above 3which can help me Cost of tools A gap in the market They don’t provide (?)an useful advantage for the firm 8 Confidential
  • 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 presentationSource: 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. 9 Confidential
  • Next steps• Finalize document for OAP submission (19 May) – Consolidate survey feedback from enterprises – Finalize proposition definition – including product features & points of differentiation – Market test proposition through face-to-face interviews – Fine-tune proposition – Pivot as necessary• Commence work on OEP – Technical foundation for the prototype is currently underway – The marketing & distribution team is working on the positioning and brand message – Financial model is being built 10 Confidential
  • Appendix 11 Confidential
  • SAJITH Team descriptionName Location Work experience Core competence EducationAlessandro Dublin 2 Years Software Engineering (C++, VHDL) BSc, MScAnthony Johannesburg 2 Years IT Entrepreneurship, Marketing and Finance Bcom (IT) South AfricaArnaud Tahiti, French 13 Years Marketing & Business development BSc, MSc PolynesiaBharath Singapore 2 Years Software Engineering, Database BSc Eng. AdministrationDeepak Singapore 8 Years Software Engineering, Machine Learning BSc, MSc, MTec TechniquesFilip Antwerp Area, 10 Years Business Consultancy BSc Eng. BelgiumMatej Slovenia, EU 10 Years Software Engineering, System Administrator BSc. MathMunir NC, USA 15 Years PLM, Business Analytics (Data Mining) BSc. Eng , MBAPatrick CA, USA 1 Year Software Engineering Reading BSc. EngRomil New Delhi, 10 Years Internet Marketing & Branding, E-commerce BSc (HM), MTM India and Web developmentSajith Singapore 5 years Software Engineering, Data Mining, BSc (Hons) Eng. SemanticsSandeep Singapore 14 years Strategy Consulting Engineer & MBA Business case development 12 Confidential
  • Why SME’s?• Empirical research has highlighted that SMEs 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 SMEs.• Most software firms aim to service the large enterprise- there is a big gap in the SME space 13 Confidential
  • About nickelring Why nickelring? You can visit us at • Nickel is a chemical element with the chemical symbolwww.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! 14 Confidential
  • 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 poorSource: McKinsey & Co online survey conducted from October 4 to October 14, 2011, and generated responses from 927 executives. 15 Confidential
  • 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 16 Confidential