Abstract Background: Internal quality control is monitoring the procedure to ensure continual evaluation of the reliability of daily work of the laboratory. This ensures continual validation of the reliability of the results produced by the laboratory, before the release of reports. It includes repeated measurement on routine samples using the control samples along with daily statistical analysis of data. Several methods are available for the analysis of laboratory quality control data like Levey Jennings chart (Westgard Rules for interpretation), Cumulative sum chart and Average of Normals chart. Laboratory testing is a complex activity, each involving a series of process steps, every one of which can result in an error. The classification of errors is based on the time they appeared in laboratory practice namely pre-analytical, analytical and post analytical stage. In the present study, we have compared Westgard rules, cumulative sum and average of normals in early identification of laboratory errors. Aim: To study usefulness of Westgard rules, cumulative sum and average of normal, as tools for internal quality control and to compare the three tools in early identification of laboratory errors. Material and Methods: Total 900 data points (quality control values or events), pertaining to each of the haematological parameters haemoglobin, total leucocyte count, platelet, mean corpuscular haemoglobin concentration and Prothrombin Time were analysed. Prothrombin time was analysed on Erba Semi Automatic ECL 105 single channel coagulation analyser and rest parameters were analysed on fully automated 5 part analyser XT-4000i. For statistical analysis of data, Levey Jennings chart and Cumulative sum chart were used for haemoglobin, total leucocyte count and platelets. Westgard rules were used for interpretation of Levey Jennings charts. Average of normals chart was used for statistical analysis of mean corpuscular haemoglobin concentration parameter. Conclusion: In the present study we have found that Levey Jennings chart is more efficient with respect to Cumulative sum chart in detecting random errors. Cumulative sum chart detects systematic errors earlier than LJ chart. We recommend use of more than one internal quality control tool for statistical analysis of data.