Growth and sustainability of a business firm is often dependent on a wide range of factors. From marketing strategies, research processes, technological advancements to adaptation of shifting business structures, the business world is operating almost on entirety of a different clock time a fact that is defining how new and already business firms are operating (Wawira, 2013). Over the past decade, technology advancement has grown to great measures bringing new definitions of business processes.
Such business processes include: production, sales decision making etcetera. Shinnick and Ryan (2008) on the role of information in decision making note that, “…the advent of the World Wide Web and other communication technologies has significantly changed how we access information, the amount of information available to us, and the cost of collecting that information.” In practice, a good information system is definitive of the business operations as well as it is key in decision making.
Unlike the tradition trial and error method of business decision making, modern decision makers are faced with the challenges of making decision which are influential of the path a business is likely to take. Whereas as good decision will oversee growth of a business, single wrong decision, is likely to cost the business firm a whole lot of resources both monetary and even worse might raise ethical concerns. However, availability of information to the decision-makers has drastically improved the process of business decision making.
Tremendous technological advancements have influenced drastic changes in business working environment. An article by the Forbes magazine (2016), argues that work environments are outcomes of evolutionary processes and as such require managerial adaptation to ensure smooth operations.
The correct information, at the right time has got numerous advantages to business organizations. Hence tacit information (Pivar, Horvat & Malbaši?, 2012). Often, study of tacit information can be tedious due to its unstructured nature unlike explicit information which is accurate and straight forward.
Considering email exchange between R, D &D staff members which is a composite type of tacit information to examine the rate of connectivity, direction and intensity of traffic (Howells, 2007).
Figure 1: email exchange between R, D &D staff
Table 1 indicates the number of clusters as well as the cluster constituents from the map of research, development and design (R, D &D) staff emails.
|
Clusters |
Nodes Identified per Cluster |
|
1 |
75,21, 67, 27, 15, 59, 74, 08 24 |
|
2 |
80, 30, 32, 70, 12, 53, 10, 54, 29, 37, 73, 58, 44, 81, 66,34, 49, 26, 68 |
|
3 |
19, 52, 35, 04, 36, 76, 14, 41,31, 13, 52, 45, 16, 48, 77, 38, 72, 69, 50, 47 |
|
4 |
83, 09, 57 |
|
5 |
61, 62, 07, 51, 65 |
|
6 |
78, 40, 39, 84 |
Table 1
|
Rooms |
Clusters |
Key Members Selected to Attend Meetings |
|
A |
1 |
75, 74 |
|
B |
2 |
80, 30 |
|
C |
3 |
19, 48 |
|
D |
4 |
83, 57 |
|
E |
5 |
07,61 |
|
F |
6 |
78, 40 |
Table 2
Clusters are selected according to their rate of connectivity (Song & He, 2012). That is, it is assumed that the initial node from which more connecting line originate from do indicate more communication to other nodes. Hence the size is dictated by the extent to which the connectivity goes. However, some nodes are interconnected to other nodes in other clusters and as such, a node is included in a cluster if it is at most three steps from the root node, i.e.
Nodes in the clusters are selected according to their extent of connectivity to the root node, such that a node that is beyond the third step from the root node is assigned to the nearest cluster where its connected nearer to the root node. However, in cluster 4 where the nodes are independent of other nodes in other clusters all of the nodes are included. In addition, a node that is in one cluster and can also be included in another cluster is only included in the cluster with least number of nodes. For instance, node 07 can be included in cluster 2 and 4 and hence is included in cluster 4.
Yes, there was an inclusion of dangling nodes which are connected to other nodes but not in connection of other cluster nodes. Interconnected dangling nodes indicate that there is some type of communication among the nodes and hence form a cluster of their own, i.e. cluster 4 is made up of dangling nodes 83, 09 and 57.
In cluster selection, there is no inclusion of unconnected nodes due to the assumption that they do not represent relational connection with other nodes that is they may be viewed as outliers in tacit information analysis hence won’t be significant in knowledge extraction (Busch, Richard & Dampney, 2003). Unconnected nodes that were not included are 28, 82, 20 and 03.
A sole source of information might be prone bias or information omission. Therefore, two staff members are chosen so as when disseminating the information gathered, they can complement, and check each other’s information for accuracy and unbiasedness.
Leximancer visualization analysis enable determination of concept interconnectedness in a qualitative dataset. Through use of thematic analysis, concepts with close relationship tend to overlap in the leximancer map.
In each organization, there are different levels and types of communication which are often dictated by the role of staff in the firm. Concepts with more interconnectivity in the ideas and related concepts are larger on the map. However, in figure 2 below, all the concepts are approximately the same size hence proximity and line connectivity are used for analysis. Additionally, co-occurrence levels are represented by collocation where proximity implies relationship levels in the explored concepts.
Figure 2:Leximancer Concept map
Generally, the purpose of communication in a firm as a major source of information to the management is supported by the overlapping of the two themes management and open. The clustering patterns and behavior are indicative of the macro-level view of communication as an effective tool of management.
The company’s field service takes a mediator form of communication. From figure 2, the team is connected directly to the management indicating there is direct interpersonal communication between the executive and staff. In addition, the management is connected to the work concept which is also connected to the team. Given such connection, it can be deduced that apart from work relationship the management has personal communication with the field service team, an approach that is different when considering the communication between the team and customers which despite being open is only work related given that there is no direct connection between the team concept in the communication theme and the customer concept.
It can therefore be concluded that the field staff members communicate with the management and the customers whereby they most likely report back to the management on the prevailing market performance, sales reporting and other factors related to their filed service, whereas they promote the products, conduct customer service support and carry out sales in their communication with customers.
From figure 1, there is high level of communication between customers and the management. Such behavioral focus is supported by the close proximity and overlapping of the open and management themes.
Ward, West and Smith (2014) argue that in a leximancer, “…the lines or pathways navigate the most likely path in conceptual space between concepts…” Hence, taking the relationship between customers and the concepts of work, team and communication in the communication cluster as indicative of the availability of support, it is evident that there is a considerable moderate level of support availability which has played an important role in ensuring openness in communication between, the management, customers as well as the staff team.
Earlier on, it was noted that apart from work related communication, there is a possible consensual communication between the management and the team i.e. taking in consideration the Ward, West and Smith (2014) supposition.
Results that are communicated by the field staff incorporate: market performance, customer concerns on factors such as product and service provision. Hence supportive in nature (they provide supportive information to both management and customers) Such information is crucial to the decision making process by the management which effects the results from the communication of the field staff. Additionally, it is through the field staff that the management can deploy their decisions to affect the company’s product provision to the customers.
Therefore, the management effects the results communicated by the field service team through related decision making. That is, making decisions based on such information hence acting as the last mechanism which makes use of the information provided by the staff through making decisions that are enacted by the staff hence. As such, they can be viewed as decision makers in results generation.
Given the above analysis:
From the above analyses involving the case scenarios on tacit information and leximancer, the following recommendations are proposed:
Scenario A
Viewing and handling of information under dynamic settings will therefore enable the company to gather accurate information as well as ease its analysis for insight gaining.
Conclusion
Information is critical in the growth and sustainability of a business organization due to its role in aiding the executive’s decision making. Therefore, having a well-defined and reliable information monitoring and collection tool is mandatory in case there is in need of unbiased information. Due to the nature of information, textual data for a while had been over looked due to its cumbersomeness in analysis and lack of statistical tools to draw data patterns to enable gaining of insights.
Tacit information analysis and the leximancer are perfect tools to enable business organizations to: group, classify and analyze textual data so as to determine underlying patterns (themes). Such data might include recorded transcript information, data gathered from interviews, etcetera. Unlike traditional view of data, as in numbers, a view which only enabled analysis of parameters such as the company’s profitability, sales pattern and other similar endeavors, the modern use of tacit information enables analysis of skills, cause-effect, cultural, emotional aspects in a business set up.
References
Busch, P., Richards, D. and Dampney, C. (2003). The graphical interpretation of plausible tacit
knowledge flows. Asia-Pacific symposium on Information visualization, 24(7), p. 37-46. DOI: 1-920682-03-1
Forbes. (2016). Nine ways work environment will change in the next 15 years. Retrieved from:
https://www.forbes.com/sites/forbescoachescouncil/2016/12/14/nine-ways-work-environments-will-be-different-in-the-next-decade/#7b0326522161
Howells, J. (2007). Tacit knowledge. Technology Analysis & Strategic Management, 8(2), p.
91-106. DOI: 10.1080/09537329608524237
Pacific Transcription. (2018). Using Leximancer for Qualitative Analysis of Transcripts.
Retrieved from: https://www.pacifictranscription.com.au/blog-leximancer.php
Pivar, J., Horvat, J. and Malbaši?, I. (2012). Literature Analysis of Transfer and Learning Tacit
Knowledge. Information and Intelligent Systems, 23(7), p. 19-27. Retrieved from: https://www.researchgate.net/publication/268058205_Literature_Analysis_of_Transfer_and_Learning_Tacit_Knowledge
Shinnick, E. and Ryan, G. (2008). The Role of Information in Decision Making. International
Journal of Decision Support System Technology, 12(3), p. 776-777. Retrieved from: https://www.irma-international.org/viewtitle/11320/
Song, G. & He, B. (2012). Model analysis of tacit knowledge transfer based on cluster network
structure features. Journal of Convergence Information Technology, 4(9), p. 312-317. DOI: 10.4156/AISS.
Ward, V., West, R. & Smith, S. (2014). The role of informal networks in creating knowledge
among health-care managers: a prospective case study. Health Services and Delivery Research, 2(12), p. 33-47. Retrieved from: https://www.ncbi.nlm.nih.gov/books/NBK374057/
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