Perspectives on baseline data collection in Makana Municipality
The seven member strong data collection team, from left to right: Akhona Mbaleki, Thabang Tanduxolo Banga, Nomthandazo (Patricia) Ntshobodi, Dalindyebo Zani, Nontsikelelo Mfecane,
Khanyisa Nqoqo, Mzwanele (Tshepo) Nkontso. Assembled in Vukani Township on the outskirts of Grahamstown ready to head off for a day of chatting to residents and gathering responses.
8:30am – the diesel engine gives two lazy turns before starting up with a heavy whirr.
It’s a chilly Monday in Grahamstown. My research partner, Thozi Ngeju and I are on our way to the Joza Post Office to meet with our team of seven data collectors.
After two, half-day training sessions on survey data collection methodology and some discussions on the use and value of MobiSAM as a social accountability monitoring application we are anxious to get going.
Armed with bags filled with printed questionnaires and a collection of digital cameras and smartphones we talk through the day’s strategy as we wind up Raglan road.
Rolling into the grassy parking lot we are greeted by the team of community-based data collectors eager to get their packs and head into Wards, 2,5,6 and 11 for a long day of asking sometimes tricky questions.
Sourced from across the town, the team members were selected on the grounds of experience, isiXhosa language proficiency and intimate knowledge of various areas in Makana.
Focused on gathering data based on a representative sample of Makana the following demographic markers of employment, race, geography and gender, were used to clump together Wards which share similarities across the Municipal area. Therefore, despite being geographically demarcated as separate and managed as separate politico-administrative entities or Wards, we came to find that there are areas which share similar markers when viewed from the perspective of gathering a representative sample of responses.
Developed as a collaborative effort on the part of the MobiSAM team, drawing on past surveys which sought to uncover similar information, the questionnaire in essence seeks to uncover from the perspective of the residents of Makana Municipality; who talks, to who, about what?
Working in Makana
“Now remember that we are looking to find a good spread of gender and age today, so please keep it in mind when approaching people,” says Thozi as he emphasizes care and focus on the task at hand.
Heading out to the various sites, each data collector is expected to locate and administer an average of 9 surveys’ a day, each survey taking about 35 minutes to complete.
Spanning a total of six days and roughly 15 sites the data collection was conducted on a tight schedule with very little room for error in a desired sample of 400 residents.
Key insights from data collectors
Describing the overall data collection process, there is unanimous consensus among the team that despite there being some challenging moments, they felt comfortable in meeting these head on, “yes there were some challenges, but they were all manageable,” said one of the team in response to a question posed as part of a post data collection debriefing session.
Another member added that to her, “it was a great, quality experience [which] helped me a lot and taught me communication skills as well as to listen to people.”
The overarching issue faced by all seven of the data collectors relates to how they were perceived when in the field, “The survey is conducted around elections, then they [community members and ward Councillors] always assume you are one of the organisations campaigning for a vote, but with a strategic approach you would win them over…”
The main challenge therefore was navigating in a sensitive, yet stern way the obstacles posed by a fractious and heightened sense of political engagement due to the a two month run up to local government elections.
This increased pressure on Ward Councillors and their constituents to draw votes and support, led to suspicion and a wary attitude by some of the residents toward the data collection team. Fortunately this initial distance was in most cases easily mitigated by the data collectors who were able to explain and contextualise their activity in the various locations.
As such the the baseline survey data collection process within the various Wards in Makana enabled us as a MobiSAM team to gather a great deal of useful data which would help us to inform and guide the next phase of engagement between MobiSAM, Makana Municipality and the roughly 80 000 people who on a daily basis rely on its administration.
@Hank0101 / https://www.facebook.com/hancu.louw
