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Building for sustainability: A Q&A about BID’s total cost of ownership tool

By Mercy Mvundura, Senior Health Economist, BID Initiative

Nov 16, 2017

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Photo: PATH/Trevor Snapp. The total cost of ownership tool estimates the financial costs of designing, rolling out, and sustaining data quality and data use interventions in Tanzania and Zambia, for the next three years.

In order to achieve the long-term sustainability of data quality and data use interventions, countries and governments must understand the financial investment to develop, implement, and sustain such tools as Tanzania’s and Zambia’s electronic immunization registries (EIRs). This information can help governments budget for and plan for expansion. We caught up with BID’s Senior Health Economist, Mercy Mvundura, to better understand the role of a total cost of ownership (TCO) tool and how it will benefit other countries interested in implementing their own digital health initiatives.

Tell us about BID’s TCO work, and our progress to date.

The TCO tool estimates the financial costs, or the money that goes into designing, rolling out, and sustaining data quality and data use interventions in Tanzania and Zambia, for the next three years. People always ask how much it costs to implement, and this is an opportunity to provide the evidence. So far, we’ve generated those estimates for Arusha Region in Tanzania.

How will this information be shared and applied to other countries, beyond Tanzania and Zambia?

This framework could be used to estimate the cost for other countries interested in similar interventions. In Zambia and Tanzania, there have been a lot of learnings, which is a big cost component behind implementation. Though these estimates are specific to Tanzania and Zambia, other countries can learn from them.

How might these cost estimates vary for other countries?

There are several examples of why the estimates may vary. One example is staffing and transportation for rollout. How far staff need to travel to implement interventions in certain health facilities impacts rollout costs. The strategies countries use to rollout the interventions may also lead to cost variations. Tanzania and Zambia used slightly different implementation strategies. In Tanzania, for instance, BID evolved its rollout strategy so that district data use mentors, or DDUMs, train health staff on the use of EIRs and other data quality and data use interventions, instead of relying on BID staff. This has cost implications. Also, if a country chooses to use a prepackaged system software rather than developing the system from scratch, that may be another difference.

The TCO tool is a live document. Why is it important to treat this as a living tool and to continually update it?

The costs already incurred won’t change. But, as I mentioned, the costs are projected for three years as there are ongoing activities. As we get better data, we will update the tool to reflect actual expenditures rather than the budget estimates, especially for recurrent costs.

Internet connectivity is one example of a recurrent cost. Another example is the ongoing costs for the server, or where the data is stored. There may be monthly or annual costs to house the data on the server. In addition, there are also replacement costs for tablets. As things break down, they will need to be replaced and so these costs will be updated as they are incurred.

Who is the primary audience for this tool?  

The main audiences are the ministries of health in Tanzania and Zambia, donors, and other countries interested in implementing similar interventions.

Do we have any early findings we can report?

System design represents one of the biggest costs among those captured in the TCO. These are the upfront, one-time costs incurred to set up the new system. The biggest cost driver of rollout is labor costs, followed by transport costs.

How is this costing data being used to improve implementation as rollout continues?

The tool is developed using retrospect data and is not a forecasting tool. However, it can be used to retrospectively evaluate the decisions made. For example, in Arusha we did switch strategies, so we looked retrospectively at the cost of either strategy. That type of data can be compared and used moving forward to inform decision-making about continued rollout strategies.

We are also planning to develop a TCO tool for Tanga and Kilimanjaro. When will these estimates be available and how will they differ from those for Arusha?

The TCO for Tanga will be available by the end of the year. The tool for Kilimanjaro will be available in early 2018. These will offer an important comparison given that Arusha was the first region where we implemented data quality and data use interventions. As it was our test region, we learned a lot and can apply those learnings to Tanga and Kilimanjaro to be more efficient. The TCO for Tanga and Kilimanjaro will reflect the rollout costs more accurately as we scale.

What are potential financial and economic benefits/savings that can be attributed to the interventions?

The TCO is just a look at the cost. To evaluate the benefits, we’re working with our monitoring and evaluation (M&E) colleagues to provide insight on whether there have been improvements to data quality, a reduction in vaccine wastage, more optimal or accurate vaccine stock levels, etc. Some of these things aren’t quantifiable financially, or in dollar terms – such as data use – so we’re working with the M&E team to capture that. The TCO is just one side of the coin.

To learn more about BID’s TCO tool, check out our factsheet.

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