Consultancy Market Shaping Indicators

For full details and submission process, please visit https:********************************************

• Reall is a UK-based investor and innovator in affordable housing in urban Africa and Asia.
• We develop, refine, and share innovative housing models that unlock the political will, capital investment and end-user finance needed to create the conditions for hard-working families to secure homes.
• Reall, is looking for a Pakistan-based consultancy to lead the rollout of Reall’s Market Shaping Indicators (MSIs) in Pakistan.
• These MSIs consist of a set of housing market focused indicators that provide a deeper understanding of a country’s housing market using data sourced from international, national, and local actors.
• The consultancy work will consist of identifying sources, collecting data, documenting the data collection process, and assessing the quality of that data using set quality standards.

Questions and Responses:

To ensure a fair and transparent procurement process, Reall is including answers to questions asked by other potential bidders below:

1. Is there an academic – practitioner mix that REALL is looking for in the applicant firm? 

Reall does not have a particular preference for academic/practitioner mix. From a tendering perspective no entity is excluded, and all are welcome to apply. We will focus on the quality of the submission when evaluating.

2. What is the scope for identifying a need for conducting some level of primary research for missing indicators? 

Based on our experience undertaking MSI work in Africa, we anticipate that a significant amount of data will be available to some extent from various public and private institutions. We envision that the successful applicant will explore multiple avenues for collecting data and filling missing indicators, and this may require creativity and ingenuity. However, we don’t expect this to include household surveys or similar for this initial iteration of the MSI work.

3. WB DBI only exists for Lahore and Karachi as per our knowledge, in case these data sets are not available for other parts of the country, how much room does that applicant have for conducting primary research? 

When undertaking MSI work in Africa, Reall and our implementing partners relied on national level data for the World Bank DBI. If there is additional DBI data available for specific cities and regions, including these will add value but is not essential to complete this phase of work.

4. IAG brings a unique skillset in terms of creating data visualizations and these are both using descriptive stats and geographical locations. Is REALL interested in the latter value addition? 

Reall is an evidence-led, learning organisation that aspires to make all data available and open source. To support this mission, Reall launched an innovative Data Dashboard in 2020 (https:********************************************). This Dashboard will be further developed to incorporate the MSI data from our priority countries in Africa and Asia, that enables users to browse and engage with the data and assess its quality. This Dashboard does not include further visualisations of the data, and we would welcome submissions that incorporate these elements when appropriate. We would encourage applicants to include this as an optional extra in the project budget, rather than as a core cost.

5. Is the applicant supposed to have an existing relationship with The World Bank? Or will REALL help with that? 

Based on our experience undertaking MSI work in Africa, we anticipate that a significant amount of data will be available to some extent from various public and private institutions. We envision that the successful applicant will explore multiple avenues for collecting data and filling missing indicators, and this may require creativity and ingenuity. A direct relationship with the World Bank may enhance and add value for this, although we do not consider it an essential competency.

6. Can you provide us with an estimate of the budget for this work, that will help build/place the team and the proposal accordingly and more efficiently?

We are unable to provide an estimated budget for this work in advance. We invite applicants to assess the Terms of Reference and propose a rational programme and budget within their cost structure.

7. We were wondering if Reall might be in a position to share with is a report from the MSI work from Sub-Saharan Africa – especially related to the primary data collection component? We are in particular interested in getting a sense of the sample size used.

Please email ********* to request a relevant document from Reall’s MSI work in Africa. This is essentially a manual for the MSIs (Headline Indicator Metadata), detailing the definitions and methodology for each indicator and the data elements that make up that indicator, along with collection frequency and suggested sources based on work undertaken so far. As this details over 100 indicators and even more data elements it is a lengthy document, but we feel this provides a strong set of instructions for adapting the approach to Asia.

8. Is there an expectation as to the scope of the primary data collection exercise?  Countrywide (including urban, semi-urban, and rural areas) or just major urban centres (and peri-urban areas)? If the latter, which ones? 

Generally, it is expected that as much data as possible is captured from secondary data sources, and for where that is not possible, a light touch primary data collection process to be utilised. It is not anticipated, for example, that household surveys would be required. A key consideration is cost and replicability. As Reall would be aiming to repeat the process each year, large sample primary data collection would be challenging. Suggested sources from the Africa work are listed in the Appendix of the TOR, but primary data sources would generally be expected to include Reall partners and other developers, real estate agents, conveyancers, planning authorities and building material suppliers. Those indicators focused on primary data would also generally be captured at city level, rather than nationally. We would expect the consultancy to recommend suitable sample sizes to ensure quality data and value for money.  

9. Also, as we are hoping to partner on the bid with an academic institution, they were keen to understand the intellectual property rights over the data/info generated as a result of this project given they would very much like to use the same for teaching purposes.

Reall is an evidence-led learning organisation, and aspires to make all data open source. The data and information generated during this project will be disseminated publicly, at the discretion of Reall. We expect that any use of the evidence generated through this project by other entities and individuals (including for educational purposes) will clearly acknowledge Reall as the provider of the compiled data, and feature Reall’s branding and logo prominently in relevant materials. Further details on the intellectual property rights and use of data will be included in the contractual agreement with the winning applicant.