REFINEMENT QUESTIONS for Employing Youth through Big Data Analysis (assimilation, categorization, classification) Open IDEO Challenge

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1 Link Edited on September 08, 2014, 05:25AM REFINEMENT QUESTION #2: What is the value (to business) of crowd-sourced, Big Data Assimilation (BDA)? This equally pivotal question speaks to the viability and sustainability of this Youth Employment concept. For, even if plenty of raw (unstructured/semi-structured) data sets are identified and successfully assimilated (whether en toto, or, a subset thereof), ultimately, the service and product (the now structured BD) must be consumed (purchased and/or utilized) by the End User of this BD. Lacking a clear, or workable, market-based valuation, the employment model/concept proposed here could fail. Now, it should be noted that nearly every business, corporate player, data analytics company, etc. agrees that BD has tremendous value for business and its (growing) existence will have major impact on how, where, and to what extent business is conducted, world-wide (note: data mining for scientific, social policy, and commercial purposes is already in full swing and being used, in the case of commerce, to guide business decisions and marketing strategies and shows no sign of stopping). These same interests also acknowledge the huge (and growing) volume of unstructured BD that begs to be used, analyzed, and applied to business activity (and also scientific research and social policy), market entry and new product development once it is transformed into meaningful information (to be processed by computers and analytics programs). So, we already have validation of the NEED for this service (as proposed here, perhaps initially following the citizen scientist model) as well as validation of its value to science (note: many BD projects have provided important data that led directly to publications in peer-reviewed journals, with zooniverse contributors cited in the credits). This BD assimilation work product has proven its scientific value (as a service focused on classifying data), and continues to prove this. However, if one were to ask the scientists who utilized this crowd-sourced (transformed) data to put some value (monetary) on the data and/or the service, they would be challenged to do this. Transferring scientific value (e.g., refined data to support scientific research and discovery) to market value is problematic. Currently, many IT corporations from Google to Microsoft are actively engaged in this BD valuation problem/question. These large entities have an advantage in that their cloud services can offer BD analytics services (including software that "finds" structured data in the unstructured data) to 1

2 companies for whatever price the business consumer is willing to pay for the service letting the End User (business consumer) determine for itself what the value of the assimilated and/or analyzed BD is. This whatever the market will sustain approach works fairly well, for now. But, as time goes on, and this data is used more and more to guide business decisions (which will then, in turn, be analyzed again for cost-effectiveness), this current payment for service only approach will likely change. And, we still have not answered the question of the value of this data (to the end user). Perhaps this is due primarily to the X Factor in business no one can predict entirely accurately how a business (product or service) will perform in a given market -- even with reams of analyzed data - and this uncertainty is reflected in BD valuation. Now here, in this youth employment concept proposal, I am proposing a service that occupies the middle ground between the generation of BD (from many sources) and its utilization by businesses (but also by social policy foundations, local and national government agencies, NGOs, consumer sciencebased commercial enterprises, etc.). Both cloud BD analytics providers and End User businesses could potentially have need of BDA services (whether in-house or outside contracted) depending on the type of data (some of which may already be structured for analysis if its source is a data program that outputs data in the desired, structured form/format). Given the acknowledged value of Big Data AND the need for assimilation of highly variable ( raw or unstructured) BD, we can safely say that the service is greatly needed. But it is the end user that determines the amount it is willing to pay and this will impact any contracting for BDA services (which will impact the payments to the BD assimilators). (Refinement Question #2 continued in next entry) 0 Applaud Team Link Edited on September 08, 2014, 05:30AM [REFINEMENT QUESTION #2, continued] Let us take a hypothetical example: 2

3 A large, or growing business (say, a supplier and/or retailer of consumer electronics) wishes to know who is buying their electronics, what items are most/least popular, as well as how satisfied consumers are with their products (which will likely influence their brand loyalty and readiness to purchase again in the future). The business has already identified a BD resource, or several resources, that it feels will help them understand/answer these questions (e.g., consumer electronics review sites/blogs, how to advice sites [typical of software trouble-shooting or Q & A forums] and also key Social Media sites that provide user/ fan forums). Let us also suppose that the business has acquired access to these sites (perhaps semi-anonymized to protect individual identities) with the result that it has several million data objects (separate posts, comments, likes / dislikes, reviews, and even purchasing data from a supplier/distributor, like As a trial run experiment, the business contracts with our BDA service to classify a subset of these BD sets say, 100,000 consumer reviews and/or comments so as to learn how satisfied consumers are (or are not) with their products and how many have made repeat purchases. Part of this contract for services will include some monetary amount for each data object classified (or just a 'labor cost' budget iline; the amount per item to be determined by the BDA manager). The contract also specifies the type of classifications desired (type of product, number of positive/negative comments, repeat consumer [ will likely purchase again ], discount/retail price purchase, competing products, disruptive trends ), the form of BD deliverables, and the time period by which the assimilation is to be finished. The BDA service agrees to execute the contract (following a User Interface design/implementation stage, so as to make the assimilation smooth and on-target to the customer s needs) with the option to renew the contract upon successful completion of the project. Once the project is completed and the now assimilated data is delivered to the business (for its own BD analysis), at some point, the business utilizes the analyzed data to make changes to its purchases (from suppliers) and possibly even changes in product engineering (to meet consumer demand) by its partnered manufacturers. Let us suppose that, following these changes (propelled by the BD analysis made possible by the BDA service), sales (of the products analyzed) increase by a healthy 2-3% over the previous (or comparable) time period (such as during a gift-giving holiday shopping season). Ok then, how then do we estimate the value of the BDA service based upon this increase in sales? Clearly, not all of the increase in sales is directly attributable to the BDA service, yet SOME percentage of the increase would seem to be related to the BDA service. Now, this amount would need to be weighed against the actual cost of the BDA contract for services; determining the cost-effectiveness of the BDA service would be key to the valuation of the service. The cost of the BDA service could be considered as part of the companies R & D or marketing research budget, and this amount figured into the company s operation budget. If sales increase (= total revenue before net profit) and the company can grow its profit margin (after accounting for/deducting the cost of its marketing budget including the BDA 3

4 services), this would show (apparent) cost-effectiveness (in this ideal case example) AND the value of the BDA service (to the business); the business value could thus be defined as some function (or factor) of the sales increase (minus cost of the service). While this does not nail down the actual value of the service, it does offer a starting framework within which to constrain upper and lower limits to its value. (Refinement Question # 2 continued in next entry) 0 Applaud Team Link Edited on September 08, 2014, 05:34AM [REFINEMENT QUESTION #2, continued] This is but one example; there are likely many other examples but I have tried to make this fairly generic so that it has broader applicability. Ultimately, the cost/valuation of the BDA service will be dictated by a combination of factors: the amount a business is willing to pay, the market (sales) return on investment (marketing research expenditure), the competitive edge (share of the market -> profit growth potential) gained by its use, competing technologies ( disruptive or otherwise, such as when mp3 players replace CD players), and also similar competitive services (i.e., other BDA services -- crowd-sourced or machine algorithm-based). One final note: A recent (2013) ideational challenge brokered by called Determining the Business Value of Big Data was offered precisely to deal with this issue. Although I was a registered solver for this challenge, and did some initial research, I did not end up submitting a proposal for it (due a competing challenge deadline). Regardless, I do not, and would not, have access to any of the winning proposals for that challenge (these are confidential to the Seeker per the Solver s agreement). Also, since there was a guaranteed winner, the selected proposal(s) may not have fully answered or addressed this issue/question, but may have only offered the best approach in the pool 4

5 of submissions as deemed by the Seeker (who was anonymous). I welcome any of your thoughts or insights on determining the value of assimilated Big Data as in applies to this youth employment concept. 0 Edit Delete Report Team Link Edited on September 07, 2014, 22:05PM REFINEMENT QUESTION #1 : How might a Big Data Assimilation (BDA) pilot program or 'start-up' gain access to BD data sets? Note: Big Data assimilation = turning 'raw' data into ("meaningful") information (that can be processed by computer programs and their algorithms) This may likely be the pivotal question going forward. Some BD data sets are publicly available (currently anyways), like twitter feeds and public agency or government data pools. Other data sets may be proprietary, as with Facebook. There are also many companies currently engaged in BD analysis. However, to what extent they use, or might use, a BD assimilation (crowd-sourced) service is unknown. In some cases, these companies may be using data that is already structured for computer processing (as with highly technical and specialized data from bio-medical research). However, as a recent Forbes article ('The Power of Big Data for SMB s' referenced in the blog listed in the following entry, below) describes it: "Big Data has many 5

6 definitions most of which can be summed up to data that is difficult to extract value from due to volume, variety, and veracity." The key terms are 'variety" and "veracity"; the variety of data (videos, photos, podcasts, blogs, comments, etc.) poses a number of challenges for computer processing. Also, by "veracity: it is meant that the data may have questionable validity or provenance, which also poses a challenge; the data may have potentially great value, but a company may be reluctant to devote its time, money and resources to analyzing it to find out. In both of these cases, it is proposed here, crowd-sourced, data assimilation may be the best way to go (even if the data set proves not useful, this too has value, and it is cheaper to use crowd-sourcing, to determine this, than in-house analysis). One of the things that people are better at than computer algorithms is determining the "context" in which the data exists (e.g., does it come from web forums, comment sections, conversations...what is the history of the comment thread? Does it from users that have provided reliable or unreliable information in the past? Etc.) Ok, back to the main focus (BD data set access). A BD assimilation pilot program, like any successful business seeking to sell its product or service, may need to have a 'sales department' that identifies likely users of assimilated BD and then contacts these potential users (i.e., companies dealing with the product or services that the data relate to) to inquire as to their need for crowd-sourced, assimilation services (this represents another employment opportunity for those youth workers who are more gifted at communications and sales). A company may be more receptive to this solution (as part of its out-sourced R & D), and would enter into a contract with the BD assimilation (BDA) service (specifying type of data classifications, time period for the project, deliverables, payment per datum, etc.). So, one way that a BDA gains access to raw data is through contracting with, or partnering with, a BD analytics company, or corporation that has proprietary control of large, unstructured, data sets. The company could also aid in tweaking the BDA User Interface (UI) so that the assimilated data comes out in a form that is useful to them. Alternatively, an adjunct component of the BDA pilot program would be a "task force" whose job it is to identify new "raw" (unstructured or semi-structured) data sets that may be amenable to the proposed BDA service. Big Data is everywhere, let's not forget, and the opportunities for analysis (from which the business value derives) are many, but mostly only to the extent that the Big Data is assimilable prior to computer analysis. Once a new BD data set is identified, our youth-powered task force would then set about identifying likely users ("interested parties") of the classified data. The sales team would then be informed and make contact, inquire about interest or need, and offer consultation (to demonstrate the service and determine any data assimilation refinements needed) and finally, offer the crowd-sourced BDA service/solution. I see a strong role for business mentorship here as well, as many of these tasks are the same types of 6

7 operational tasks that most every company must utilize or implement at some point. Business consultants (especially those involved with big data analytics) may be open to helping the pilot program (for simple social good, status, prestige, etc.) "get off the ground" through offering organizational tips concerning the aforementioned tasks that surround the BDA service. Lastly (for now), the publicizing and promoting of a youth-centered, crowd-sourcing, Big Data assimilation program may encourage businesses to give it a try (the "social good" effect) and thus help the pilot program establish itself and prove itself. 7

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