EECi recently planned and launched a new and unique global enterprise survey called BESTIN-OPMES (for Benchmarking Strategy and Innovation – Operations, People, Money - an Enterprise Survey). This initiative aims at creating a data set of 120,000 cases, representing the population of businesses in a statistically reliable manner. BESTIN-OPMES is expected to expand gradually to 187 countries in 5 overlapping waves. BESTIN-OPMES aims at becoming the largest and most comprehensive data set on businesses in the world.
In 2012, EECi started developing and testing a comprehensive enterprise survey tool called BESTIN-OPMES. The questionnaire was conceived as an instrument mid-way between a questionnaire to conduct full case-studies of enterprises and a long-form enterprise survey. The BESTIN-OPMES tool has regularly grown in depth and detail in the last few years. The BESTIN-OPMES now stands at over 2,700 variables spanning over a 70-pages questionnaire.
EECi has developed CAPI, CATI and CAWI versions of the tool. As in most of our surveys, the CAPI version is the main method used to capture the answers of respondents.
EECi proceeds in a collaborative manner with National Statistical Organizations (NSOs). This consists in offering to deliver a fairly detailed presentation of the envisaged data collection in the country to the NSO, offering to interact and allow for fruitful exchanges with NSOs to facilitate high quality data collection, to the extent possible, planning our calendar in a non-disruptive manner of any NSO planned data collection exercise that we are informed of, sharing our experience in the data collection process once the survey is finished and finally offering, whenever possible, to take-on observers from the NSOs that can interact with our senior team, without disrupting the data collection itself. This said, BESTIN-OPMES is not be implemented via NSOs to ensure candid responses to the numerous delicate questions it contains, such as questions on graft, corruption and compliance to regulations.
EECi prides itself in having had thousands of surveys across the world for its clients for which a wide variety of QC controls have been executed. BESTIN-OPMES is no exception. From the verification of sample frames, to call-backs post surveys, to internal consistency tests implemented in the course of the surveys (particularly in the CAPI format), some of them disclosed to interviewers, some of them kept confidential, and only discussed post survey with respondents, to out-of-bound and outlier verifications, and to controls with other reliable published data, BESTIN-OPMES mobilizes an array of QCs prior to considering that data collection is completed and ready.
The statistical universe covered by BESTIN-OPMES is composed of all non-agricultural private sector entities with 5 employees or more, officially registered in the country of operation. Sample frames in targeted countries collate information from previous sample frames assembled by EECi in those countries, frames from business registries, Chambers of commerce and/or numerous business associations. The sampling strategy of BESTIN-OPMES allows for the integration of panel respondents to the extent possible.
The BESTIN-OPMES tool has been tested by EECi in numerous parts of the world (covering Asia and Oceania, Eastern Europe and Eurasia, the Middle East and North Africa, Sub-Saharan Africa, and Latin America and the Caribbean). Our beta-test data set used to refine the tool and develop our benchmarking interface, contains about 3,000 cases, of which 1,100 cases contain panel data.
BESTIN-OPMES created an ad-hoc advisory group of stakeholders who represent specific preoccupations inherent to the stage of deployment of this global survey. For instance, EECi invited NGOs and other specialized entities recognized for their understanding of micro businesses, or of gender issues in business/income generation activities, or of MSME financing or provision of extension services. These advisory members interact with EECi to improve or refine the tools, the benchmarking interface, or any other aspect of BESTIN-OPMES
EECi, in collaboration with its university partners, has designed a benchmarking system, which will be freely available to respondents of BESTIN-OPMES, and is continuously enriched as BESTIN-OPMES progresses. This benchmarking program is very ambitious and has currently no equivalent in the world. The few systems that exist, present in general simple comparisons of indicators of a single entity to a group of selected comparable cases. BESTIN-OPMES will go much farther, and deeper than these fairly simplistic systems.
EECi has created Users’ Groups of owners / C-Level managers of enterprises of various sizes in various developing and emerging countries, to test the usefulness, relevance and interface of the benchmarking system. It is planning on enlarging the group of business users as BESTIN-OPMES progresses. Members of the Users’ Groups will be provided with free access to the benchmarking system.
In every country in which BESTIN-OPMES is deployed, EECi implements a comprehensive awareness campaign. EECi maps institutional players, business associations, private sector development projects or implementing agencies, and media.
BESTIN-OPMES is adding a novel dimension to the quality control of the data collected. Post-survey, EECi will generate a summary presentation of the answers of respondents in a format that will not only contain straight answers, but also estimations inferred by the answers collected. This summary document is used for validation with selected respondents.
BESTIN-OPMES is managed by EECi’s senior survey core team. Together they have led the bulk of surveys delivered by our firm in recent years. This core team has been working together for years, and all members are familiar with the intricacies of our firm’s strict enterprise survey protocols.
In addition, the survey execution team for BESTIN-OPMES includes, in every country, a group of national professionals who may have either contributed to EECi’s mandates in the past, or who will have received specific training in line with the requirements of BESTIN-OPMES.
Gradually, country by country, the data sets of BESTIN-OPMES are cleaned, anonymized, and finalized for use.
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