SmartLQA Guidelines

SmartLQA is a digital platform built to simplify the use of Lots Quality Assurance Sampling (LQAS) for program teams. It helps managers move quickly from data collection to decision-making, without the delays and complexity of large surveys. This guide explains how SmartLQA works in practice and how teams can use it effectively across the full survey cycle.

Understanding LQAS and When to Use It

Lots Quality Assurance Sampling is a rapid monitoring method used to classify geographic or administrative areas as meeting or not meeting predefined coverage targets. Rather than producing highly precise prevalence estimates, LQAS focuses on identifying problem areas early so that corrective action can be taken. It is widely used in health, education, nutrition, and other social-sector programs where timely decisions matter more than statistical perfection.

SmartLQA is most effective when questions are binary, the target group is clearly defined, and program teams are prepared to act on the results. It is not intended to replace large surveys but to complement them between rounds or during implementation.

The SmartLQA Workflow at a Glance

A typical SmartLQA exercise can be completed in about three days. The first day focuses on project setup and survey design, the second day on data collection and monitoring, and the third day on review, interpretation, and action.

Getting Started: Registration and Project Setup

To begin using SmartLQA, an administrator or program lead registers on the SmartLQA website using an official email address. Website access is intended for users who design surveys, manage projects, and review results. Data collectors do not need to register on the website.

After signing in, the user creates a new project by providing basic information such as the project name, sector, topic, overall goal, and one or more objectives. Each project can include multiple rounds of surveys, depending on the selected subscription plan. This structure allows teams to track progress over time within the same project.

Designing the Methodology

For each survey round, the methodology is defined by specifying the country, catchment area, number of supervision areas, the level of supervision area such as district or block, and the sample size per supervision area. SmartLQA uses a default sample size of nineteen per supervision area, which is suitable for most LQAS applications, though users can increase this when needed.

In many real-world settings, a complete sampling frame is not available to draw a simple random sample. SmartLQA therefore supports multistage sampling. Users upload supervision area and community population data using a standard Excel template. Based on this information, the system automatically allocates the number of samples to be collected from each community.

The system also generates random numbers to guide field selection. These can be regenerated at any time. As a best practice, users should avoid clustering too many interviews in a single community. If several communities show more than three or four interviews, it is advisable to either increase the sample size or divide large communities into smaller geographic units.

Designing the Questionnaire

Once the methodology is finalized, users move on to designing the questionnaire. All questions in SmartLQA must be binary, with a clear Yes or No response. The Yes response should always represent the positive or correct outcome. For each question, the user sets a coverage target, which SmartLQA uses as the decision rule during analysis.

Optional settings allow users to enable GPS location capture or collect personally identifiable information, but these should only be used when strictly necessary. Questionnaires should be kept concise, ideally with no more than ten to fifteen questions, so that a single interview can be completed within fifteen to twenty minutes.

It is important to design questionnaires around a single target group. If different target groups are required, they should be managed as separate projects. Users must also ensure that informed consent is obtained according to their research protocol and approval requirements.

Distributing the Survey and Assigning Data Collectors

After the questionnaire is finalized, data collectors are uploaded using a standard template that includes their name, email address, and phone number. These details must match the credentials the data collectors will use in the SmartLQA app.

Data collectors are then assigned to specific communities using simple dropdown options. As a rule of thumb, no more than ten interviews should be assigned to a single data collector, and each supervision area should ideally have at least two data collectors assigned.

Data Collection in the Field

Data collectors use the SmartLQA Android app to collect data. Once assigned, they receive both an in-app notification and an email with survey details. Data can be entered directly through the app, which supports offline data collection, or through a web browser using the link provided by email.

When the app is used offline, data are automatically synchronized once the device reconnects to the internet. Data collectors can clearly see which communities they are assigned to and how many interviews are required in each location.

Monitoring Progress and Providing Support

During data collection, administrators can monitor progress in real time through the SmartLQA dashboard. The system shows completed and pending interviews by supervision area and allows admins to send reminder emails directly to data collectors when needed. This enables timely support and helps ensure that data collection stays on track.

Reviewing Results and Using Outputs

Once data collection is complete, SmartLQA automatically analyzes the results. Each indicator is classified as pass or fail based on the predefined decision rule. The platform also compares supervision areas against the population-weighted catchment average.

Users can view detailed tables showing catchment-level coverage estimates with population weighting and ninety-five percent confidence intervals. Raw data, tables, charts, slides, and preliminary reports can be exported for further use. When presenting or publishing results, users are encouraged to acknowledge SmartLQA as the analysis platform.

Dashboards and Trend Analysis

For subscription users, SmartLQA includes interactive dashboards that allow comparison of results across survey rounds. These dashboards show trends in coverage at the catchment level and pass or fail status over time at the supervision area level. This functionality supports adaptive management by helping teams understand whether actions taken after one round led to improvement in subsequent rounds.

SmartLQA is designed to support learning and action, not just reporting. Its greatest value comes from disciplined design, repeated use, and deliberate follow-up based on results.