“The engine to my comprehension is just too complex, much too complex”
De La Soul The Bizness Stakes is High Album
Introduction
The primary aim for this research was to answer one question; which is how the sugar industry would look within a ten year period and how this may affect Bosch Projects. This question had other sub-questions embedded in it; which are:
How does the future of BP look in the next ten years; when viewed through scenario planning relative to the sugar industry?
After application of SP would any of these organizations apply SP for future strategy making?
Relative to traditional strategy making methodologies how do these organizations view SP?
The last two questions could only be answered post the scenario planning exercise and therefore necessitated that I re-engage the participants to get post research feedback. Another unplanned question that emerged in the research, as I highlighted in the previous chapter is whether Bosch Projects was qualified enough to develop meaningful scenarios for the sugar industry, taking into consideration that it is their biggest market and that a number of employees are former sugar industry people.
During the actual research phase it quickly became evident that we had to look at how SA would look in ten years. We then had to imagine how that state of SA would impact on the sugar industry and ultimately on BP. The data collected came in clusters from the different organizations engaged during the research and these were all grouped to form the basis for formulating the scenarios. As previously stated the data was collected and grouped into two clusters, one for the sugar industry respondents and the other for BP respondents.
Figure 13 shows the processes followed for the data collection and analysis stages.
Seidel (1998:2) simplifies qualitative data analysis and describes it as a symphony of three notes
“Noticing, Collecting and Thinking”. He further asserts that in the symphony one should make some type of sense out each collection; look for patterns and relationships within and across the collections and make general discoveries about phenomena one is researching.
Answers to the questions asked and analytical insights that emerged during the data collection are the two points which he says one must draw conclusions from.
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Insightful Answers
Noticing
ObviousAnswers
Collecting Thinking
Data Analysis
Figure 14: Data Analysis Approach Inspired by: Patton (2002)
In this chapter I will present the scenarios developed from the sugar industry scenario planning sessions and then follow it up with the scenarios developed from the revised Bosch Projects scenario planning session. From these scenarios I will then answer the first two and the last, of the five research questions and their implications for the research participants. From post research engagement I will then answer the remaining two questions.
In the succeeding sections I will also analyse the data, draw the obvious conclusions and then highlight hidden conclusions which can only be seen through insightful analysis of the data obtained during the research as recommended.
Current State of Sugar Industry
In this sub-section I will discuss the current state of the sugar industry which is mostly informed by:
The Rich Picture which I had developed post the flawed BP scenario planning session as stated in the previous chapter.
The results of the SWOT analysis
This analysis is also informed by the multiple discussions I had with the sugar industry participants during the interrogation and analysis of the primer questionnaires. The rich picture was not used with any of the research participants but was a tool I used for myself in order to distil and summarize the issues affecting the sugar industry for my own understanding. I also could refer to it on a regular basis as I analysed the various bundles of data collected and also when I revisited and reviewed the scenarios developed at the different stages of the research. I will start off this section by providing the rich picture and then proceed to the discussion by providing the results of the SWOT factors in tabular format. These factors are grouped as presented to me by the industry participants. No factors were moved or shifted to a different column even though some had been misallocated. On analysis of the factors it became clear that there was some misunderstanding with some participants as to how SWOT factors should be grouped. Some individuals had difficulty with understanding how to differentiate the external factors from internal factors.
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Figure 15: Rich Picture for Environmental Analysis
The Rich Picture shows the main components/ agents of the sugar industry system. These agents vary across the SPECTRE spectrum and include crime, skills availability and EE, sustainable energy sources, biofuels, land ownership etc. As previously stated, the picture was for my own use as it helped me easily identify the major agents of my system of interest.
The following table is an assembly of the factors as submitted and without re-allocating factors I have drawn up the current state of the industry.
SA Sugar Industry
B.E.E.
EU Preferential Pricing &
Influence Over the Sugar Industry Land Ownership
Ethanol Production Facilities
No. of Sugar Mills and Locations
Economic Impact of Apartheid in SA Skills Distribution / Employment Equity
Sustainable Energy Sources Alternate Fuel Sources Crime: Greed & Violence
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