Patent Application
20130197970
The present invention generally relates to the use of social networks within a business and, more particularly, to application of social network analysis to improvement associate productivity and satisfaction.
A traditional approach to monitoring the general state of satisfaction of those associated with a business has only been to use static and infrequent surveys which also carry substantial expense and are of very questionable reliability. Responses to such surveys are very likely to be biased by the apparently probable response that an individual perceives would be preferred by the business, particularly if the survey is not performed under assurances of being conducted anonymously. On the other hand, a survey conducted anonymously will lose information in regard to the satisfaction level of specific individuals that the business may be able to address.
These approaches have very low value in providing real-time understanding of associate satisfaction or addressing potential issues of changes in satisfaction at an early date when action may be more effective in achieving improved productivity. The problem is further complicated by the fact that the obtaining of information by the business that may support improvement in conditions and increase of satisfaction may be deemed to be intrusive and a direct detriment to job satisfaction.
Additionally, there may be additional social factors that affect associate satisfaction. It is to be expected that a high level of collegiality, friendship and empathy among closely associated individuals should increase satisfaction. Similarly, satisfaction with some aspects of business circumstances may be spread among individuals that are associated with each other.
It is therefore an object of the present invention to provide a methodology and monitoring apparatus to provide a real-time increased understanding of associate satisfaction through a combination of behavioral analytics, deviation detection and social network analysis.
It is another object of the invention to provide a management tool with a real-time satisfaction evaluation system.
In order to accomplish these and other objects of the invention, a method is provided of evaluating likelihood, within a population of persons, that members of said population will respond to encouragement or incentives comprising steps of identifying a plurality of peer groups within the population selected to have similar responses to each of a plurality of factors common to the population, evaluating members of respective peer groups in regard to respective factors to obtain a baseline or distribution, scoring members of the peer group based on the location of the evaluation of a member of a peer group relative to said baseline or distribution for the factors within the peer group to form peer group member scores, and combining the group member scores and determining likelihood of responsiveness to encouragement or incentives from scores significantly higher or lower than an average or median of group member scores within the peer group, including configuring a computer to perform such steps. The result of such analysis is preferably refined by performing a prospective analysis by repeating the scoring process and comparing current scores for individuals with previous scores for individuals and projecting a spread of influences within the population by overlaying results of the historical analysis and/or the prospective analysis with results of a social network analysis of the population.
The foregoing and other objects, aspects and advantages will be better understood from the following detailed description of a preferred embodiment of the invention with reference to the drawings, in which:
Referring now to the drawings, and more particularly to
As a general overview, prior to a detailed discussion of the invention, the present invention is comprised of two principal analysis components, in combination: a historical analysis supplemented and leveraged by a prospective analysis based on outlier detection and scoring that can be carried out on a real-time basis and a social network analysis that serves to project a quantitative portion of a (sufficiently positive or negative) satisfaction score of interest on social network cohorts.
The historical analysis is performed over a group of individuals and provides a quantitative statistical distribution of behaviors of individual members of the group in regard to attributes of circumstances that may have a bearing on satisfaction. A satisfaction score for individuals can thus be derived based on variance from a statistical average or mean of individual behaviors. A preferred algorithm for performing this technique is provided in U. S. Published Patent application 2009/0228233A1 which is hereby fully incorporated by reference although other algorithms may be suitable and can be used in the successful practice of the present invention. In any case, such a methodology and the results thereof become far more meaningful when performed over a peer group of individuals that appear likely to exhibit changes in behaviors which are similar to each other in response to particular events or changes in business or individual circumstances, as is preferred in the practice of the invention. Choice of such a peer group (e.g. mechanical engineers, electrical engineers, analysts, support personnel, clerical personnel, etc., possibly also limited to distinct operations of the business) tends, on the one hand, to stabilize the distributions of behaviors as the historical analysis is performed and the results updated from time to time and, on the other hand, selection of such peer groups tends to make the distribution of behaviors more nearly conformal to a standard distribution curve which simplifies the computation of individual satisfaction scores and provides an increased level of confidence in the results of the scoring process, as will be discussed in greater detail below.
Prospective analysis is essentially a substantially real-time repetition and updating of the scoring process for individuals in particular peer groups based on the information derived by the historical analysis and detection of changes in individual satisfaction scores that may provide an indication of an opportunity for providing support and/or encouragement that may lead an associate to higher levels of creativity and/or productivity. Significance of magnitude of any score change can be determined empirically in regard to any and all behaviors that may be tracked in the historical analysis.
It should be appreciated that historical analysis can, itself, provide valuable insight into satisfaction at the time it is performed sufficient to support intervention in the case of high (and possibly low) scores that significantly deviate from the average or mean score for one or more satisfaction factors within a peer group at and shortly after the historical analysis is performed. The prospective analysis provides a supplement to the historical analysis in that it can be repeated frequently with a relatively low computational burden to detect changes that may correlate with particular events or subtle changes in the environment of the associate of a peer group. A frequently repeated prospective analysis can also detect trends for individuals and trends for changes in satisfaction levels between peer groups. Such types of changes in satisfaction level could also be detected by repetitions of the historical analysis but with increased granularity (due to less frequent repetition as practicality dictates) and computational burden.
Finally, social network analysis within the business is performed and overlaid on the results of the prospective analysis to project potential influence of one associate that exhibits a score change on others with whom the associate may be in frequent social contact. That is, if a given individual exhibits a potential opportunity for improved performance, others with whom the individual may be more or less closely associated may exhibit some degree of similar opportunity.
More specifically, as illustrated in
As alluded to above, it is desirable to perform analysis of these factors in regard to peer groups that are chosen based on a likelihood of having similar responses to such factors. For example, one (or more) peer groups might be entirely or predominantly electrical engineers while one (or more) other peer groups may be entirely or predominantly mechanical engineers while yet other peer groups may be predominantly from one or more support, design, marketing, information management and the like groups. It is considered to be preferable that these peer groups be selected from across the entire population of associates of the business and not limited within, for example, a particular project or product production area because the social network analysis which will be overlaid upon the result of the historical and prospective analyses, as will be described in detail below, will account for interactions within such specific operations and events within such specific operations may tend to skew and/or reduce stability of statistical distributions of data in regard to the satisfaction indicator factors 10 discussed above as compared with peer groups selected from across the entire business on the basis of similarity of likely response to conditions or events. It is also more likely that the results of analysis of satisfaction indicator factors will conform to a standard (e.g. Gaussian) distribution if peer groups are chosen across the entire population of the business.
It is desirable that the peer groups be large enough that the statistical distribution of value of particular factors for the peer group to be substantially unaffected by changes in one or more satisfaction factors for any individual. It is not required that an individual be a member of only a single peer group and an individual may be included in more than one peer group or even divided between one or more peer groups (e.g. on a weighted basis).
Once the peer groups have been determined, as indicated at 30 of
As also illustrated in
Using the distribution curve 210 and scoring curve 220 for each factor for each peer group, a composite satisfaction score is developed for each associate as depicted at 50 of
It should be appreciated that the historical analysis described above is capable of providing substantially improved information about satisfaction than has been available prior to the present invention. That is, extreme composite or individual factor scores (e.g. in the upper or lower quartile of all scores in a peer group or across the population of all or a significant portion of associates of the business) are themselves relatively reliable indicators of likely candidates for having performance improvement potential whenever the historical analysis is repeated or updated, particularly when leveraged by overlaying social network analysis thereon as will be disclosed below. However, the results may be somewhat generalized and may not be adequately timely or sensitive to current conditions and events within the business. Therefore, in accordance with the invention, it is preferred to leverage the historical analysis described above with a prospective analysis which will now be described with further reference to
The prospective analysis provided in accordance with the invention is intended to leverage the historical analysis in accordance with the invention as described above to provide near-real-time information. This further analysis is prospective or predictive in the sense that there will generally be a time lag between the event or change in circumstances that may cause a change in satisfaction and an actual change in the satisfaction level of a given associate. Therefore, prospective analysis provides a good and timely predictor of individuals who may become good candidates for improved performance upon suitable encouragement.
The prospective analysis 60 provided by the invention is quite simple and can be rapidly performed based on data developed during the historical analysis discussed above. Simply put, on a relatively frequent or event driven basis, the individual satisfaction indication factor scores and the composite satisfaction score (but not the distributions for factors within peer groups) are re-computed and updated in the manner discussed above for all or a group of associate and the results compared to the score results previously computed and stored as illustrated at 60 of
Additionally, the inventors have recognized that the influence of other associates is likely to be of substantial importance in regard to any particular action taken or contemplated by an individual. Accordingly, as illustrated at 70 of
The resulting scores as modified by the information from social network analysis as illustrated at 82 can then be evaluated and, optionally, sorted by magnitude to identify individuals and groups that are candidates for some action, as illustrated at 80 of
In view of the foregoing, it is seen that the invention provides a system and methodology for identifying individuals whose satisfaction is subject to change in response to particular circumstances and events and individuals for which intervention may prove beneficial. The system and methodology in accordance with the invention thus provides a substantially real-time system for a business and can provide a tool for increasing productivity and performance of associates of a business.
While the invention has been described in terms of a single preferred embodiment, those skilled in the art will recognize that the invention can be practiced with modification within the spirit and scope of the appended claims.
