2019Case9Roadbridge

38 L EAN C ONSTRUCTION I RELAND A NNUAL B OOK OF C ASES 2019 Figure 2. Pareto Analysis of Order Entries by Item Type The Pareto showed us that there were four types of order entries making up the top 80% of orders during 2018. Table 1. Findings from the Pareto Analysis of Order Entries by Item Type The entries for concrete and stone make perfect sense as they are a prime constituent of any civil engineering project, but the MATR00001 entries warranted further analysis, particularly as it accounted for 12.19% of entries. It was then discovered that this item type had begun to be used as a miscellaneous item, and, rather than entering the correct detail for purchase orders line-by-line, the information was being added in one line, as MATR00001, which told the person looking at the order nothing unless they could see the attached invoice from the supplier. The accounts team at Head Office would only add the invoice later, and so it was not always available. A further Pareto Analysis was conducted on the projects where the ‘MATR00001’ item type was being used the most, to see which projects were the worst offenders and where our efforts to provide a solution would need to be focused. This Pareto highl ighted that there were s ix projects that contributed to 80% of the orders being incorrectly added to the system. Figure 3. Pareto Analysis of MATR Cost Code Per Project Goals/Targets Once the extent of the issue was established, it allowed the team to develop a Gantt Chart for the implementation of a solution and for the setting of targets. The targets that were set for the programme were as follows: • To reduce wasted estimating time over an 88-day tender by 15 days. • To reduce the use of the MATR00001 item type code to 5% from 12.19% by February 2019. • To increase confidence in the data being produced by the ERP and utilise this information in a tender submission. Root Cause Analysis In consultation with the estimators at Head Office and with several site administrators, a Root Cause Analysis and a Cause & Effect Analysis were undertaken. This was carried out as a team event at Head Office, and again it was stressed that all views could be discussed openly and honestly in a blameless environment. Figure 4 highlights the results of the Five Whys Root Cause Analysis, showing that the root cause in this case was insufficient site administration staff in place on these busy projects. Figure 4. Five Why Analysis on Estimators Not Using the System Cause & Effect Analysis As an added exercise, and to determine if the same root cause would surface, the group also carried out a Cause & Effect Analysis, followed by Cause Screening, and this analysis flagged the same issues. Figure 5. Cause & Effect Analysis