The overall marks should be considered in line with the school’s policy, on interpretation of marks at the postgraduate level. Table 1 below lists the topics and their contribution to the final mark. The accompanying Grade Descriptor gives more detail on how to achieve the marks under each topic.

Table 1: Task and contribution to mark

Task Marking weight
Discrete Event Simulation modelling 40%
Analysis and insight 40%
Report 20%

For each part marks are given according to the following guidelines:

  • Context & background: Assumptions are clearly stated, properly supported by references;
  • Methods, tools and software are chosen appropriately;
  • Critical analysis, convincing arguments developed;
  • Results, conclusions and limitations are clearly stated and discussed.

The coursework will test the following four areas.

Developing Knowledge and Understanding

  • A systematic, in-depth understanding of the development; issues and influences relevant to discipline of Management Science, Operational Research and Supply Chain Analytics.
  • Deep and thorough understanding of quantitative analytical methodologies and hands-on experience with decision-making software and analytical tools.

Cognitive (thinking) skills

  • Demonstrate deep learning, understanding of the material and ability to apply the knowledge and demonstrate skills in problem solving in the topic space of the module studied
  • Collect and carry out assessments of data, select the appropriate analysis tools, design and execute an analytical methodology, apply adequate visualisation methodologies to present the results and interpret the findings and finally to communicate the results effectively.

Practical & transferable skills

  • Demonstrate the ability to independently evaluate critical approaches and techniques relevant to Business Analytics;
  • Know and apply a range of techniques and tools to analyse data related to business operations;
  • Capability of selecting the right methodology and software to solve management and operational business issues;
  • Relate existing knowledge structures and methodologies to analytical business challenges;
  • Key / transferable skills An ability of demonstrating competence in a range of skills that are relevant to the needs of future professionals concerned with Business Analytics; critical thinking, analysis and synthesis; using computer software for extracting information out of structured and unstructured data; reasoning; problem solving; independent research; presentation; report writing.

Synthesis and Creativity

  • An ability to conduct operational research and produce a high-quality coursework – this includes the ability to critical investigate, to select, define and focus upon an issue at an appropriate level; to develop and apply relevant and sound methodology; to apply the methodology to analyse the issue; to develop logical conclusions and recommendations; to be aware of the limitations of the work;
  • An ability to identify modifications to existing knowledge structures and theoretical frameworks and therefore to prose new areas for investigation, new problems, new or alternative applications or methodological applications.

TASK – Process optimisation


Police forces across the UK use Crime Scene Investigators (CSIs) to collect forensic evidence from crime scenes. Matching fingerprints or DNA to people on existing crime databases usually take around a week or two with current technologies. Newer digital and DNA technologies mean results can be gained from this forensics evidence faster than ever before. Digital fingerprints can be processed in minutes, and DNA samples can be analysed in hours rather than days. However, such rapid turnaround times requires a change in the way forensics labs operate, which are usually set up to deliver fingerprint matches for petty crimes, such as burglary and theft, within a few days and DNA matches within a week.

A trial of these new, faster technologies (Digital Fingerprinting and Rapid DNA) was undertaken by West Yorkshire Police (WYP) in 20171 and digital fingerprints have now been introduced into their forensics process. However, Rapid DNA required more development due to the sensitivity of the test. Using lessons learned from the previous trial, you are now charged with assessing the operational performance of Digital Fingerprints and Rapid DNA technologies.

Topic 1: Operational characteristics of the Digital Fingerprints process

In the traditional fingerprinting process a CSI dusts for fingerprints; if they find one they literally use Sellotape to take a physical imprint of the fingerprint! A handwritten form is then completed to take notes on the sample. The physical sample is transported back to the police station and the form manually input into the system by the CSI. The sample is then transported to the force’s forensics lab before a photo is taken of the fingerprint and it is uploaded into the digital fingerprint ID matching database. Each of these steps requires significant waiting time (for example, waiting for the CSI to return to the station, waiting for the transport to the lab, waiting in the queue to be input into the Fingerprint ID database).

In the Digital Fingerprinting process, the CSI still dusts for prints, but now has a camera with a 4G network card inside it. A photo of the print is taken and the file of that print is immediately sent to a database at the forensics lab. Still at the crime scene, the CSI fills in the accompanying form on a tablet, which also has a 4G card in it. Once the crime scene form has been uploaded to the system the fingerprint photo file is immediately sent to the Fingerprint ID database for matching.


1 crimefighting/

Given historical crime patterns in your area, you estimate that there is, on average, a petty crime every 16 minutes (exponentially distributed). The trial data from WYP suggests that it takes, on average, a CSI 60 minutes to travel to a crime scene, take a fingerprint and send off the photo and the accompanying form (again, exponentially distributed). Assume CSIs are available 24 hours per day, 7 days per week.

  Text Box: Tasks – Comparison of analytical and numerical solutions for Digital Fingerprint process 1. Use an M/M/c queueing system to analytically determine the operational characteristics of the digital fingerprinting operation. 2. How many CSIs are needed at any one time to meet the demand generated through petty crime? 3. Simulate the same system using Discrete Event Simulation (DES) and compare the numerical solution to the analytical solution to make sure that your answers are correct. You should present the average of the simulation result, plus the lower and higher 95% ranges. The analytical solutions should lie within the lower and higher 95% range of the numerical solutions. a. Use the random number seed allocated to you by email.

Topic 2: Optimising the Rapid DNA operational process

The current DNA matching process

The current DNA matching process is as follows. First, a petty crime is committed. One of a group of CSIs attends the scene and if any blood or saliva evidence is available it is swabbed and taken back to the station by the CSI at the end of their shift (see Figure 1 for an overview of the process) 2. The CSI must input all the information regarding the forensic evidence they have collected during the day into the forensics system. The DNA samples are then transported to the lab. The samples are first prepared, before being put in a queue for the DNA sequencer machine. Current DNA extraction machines are slow but very accurate, and can process up to 100 samples in one sequencing process. It takes 2 days to run the DNA sequencer, so the machine is run twice a week, once on a Wednesday morning, and once on a Friday afternoon to maximise the number of samples that can be run at one time whilst not unduly delaying results.

Each sample run through the sequencer must be validated by a senior lab researcher before it is sent to the ID database for matching. Only 2% of samples are matched to profiles on the database.


2 Serious (violent) crimes – e.g. murder, rape – are already prioritised through the system and the lab technicians won’t wait to run the DNA sequencer. For this reason, serious crime scene samples are dealt with through a separate process, which is beyond the scope of this task.

A Simul8 file of the current DNA matching process is included in the coursework material3. More detail of the process is given in Table 2 below.


Figure 1: Current DNA matching process, from CSI visit to identifying a match in the national DNA database.


3 “Current_process.s8”.

Table 2: Detailed parameter estimates for the current DNA matching process.

Stage of process Number of activities Time taken to complete activity (minutes) Schedule Collection type Notes
Generation of crime scenes with DNA samples 1 Inter-arrival time is Exponential(100) 24/7  
CSI visit 3 Triangular(50,60,75) Mon-Fri 0800-1500  
CSIs input evidence into system 1 Fixed – 60 minutes Mon-Fri 1500-1600 All  
Transport to lab   Samples 1     1 Uniform(100,130)     Uniform(10,30) Mon-Fri Collection @ 1600 Mon-Fri All     –  
are prepped     0800-1500    
  DNA sequencer machine run   2   Fixed – 2880   Wednesday @ 0900 Friday @ 1500   All   Can hold up to 100 samples in one run
Validation       DNA 1       1 Uniform(1,2)       Uniform(1,2) Friday 0900-1200 Monday 0900-1200 Mon-Fri –       –         2% of
sequence run through ID database     0800-1500   samples matched to profile on ID database
Text Box: Task – Analysis of current DNA matching process 4. Using the accompanying Simul8 file, extract relevant results for the current operational system (e.g. time in system, number of samples in a queue, time in queue). Using separate graphs/tables, identify the bottlenecks in the system that delay the samples from being matched. a. Run 500 trials, using the random number seed allocated to you by email. b. Referencing other units such as hours, or not referencing units at all, will attract a zero mark for this task. c. Not referencing the low and high 95% range will also attract a zero mark for the task. 5. According to the average times in queues and activities, identify the main stages of the system that delay the samples from being matched.

Rapid DNA matching process – various scenarios

In a similar vein to Big Data and the development of silicon chips, DNA sequencing has dropped in price and massively improved in speed over the past couple of decades. The first sequencing of a human genome took $13bn and 13 years. Such sequencing can now be done in a day or two for hundreds of pounds. As a result it is now possible to speed up the forensics DNA sampling process with new technology. New Rapid DNA sequencing machines are available, which can sequence a DNA sample in two hours. However, there are a couple of trade-offs to gain this speed: one, the accuracy and reliability of the machines is not as good as current slower machines; and two, the cartridges used to load the Rapid DNA machine can only hold eight samples, rather than 100 samples in the older ones.

Clearly, to be able to maximise the speed advantage the whole forensics process may need overhaul, as the current process is designed to deliver DNA matches en masse in about a week, not in small batches within 2 hours. Thus, on the next couple of pages, I describe a few scenarios that outline process changes that may improve the speed of delivering results.

Scenario 1 – simple replacement of old sequencers with new Rapid DNA sequencers

In this scenario the older DNA sequencer machines are replaced with newer Rapid DNA machines (see Table 3 for differences in specifications). As the Rapid DNA machine can only hold up to 8 samples at a time, the lab has made the decision to simply run the machine when there are enough samples to completely fill the cartridge. This means that there is less waiting time for samples to be run, but only eight can be processed at one time.

To monitor the Rapid DNA machine and prevent processed sequences waiting a long time for validation, the lab has employed extra staff to ensure that samples can be processed quickly. Therefore, validation now takes place as and when samples are ready throughout the day, rather than on Friday and Monday mornings. Validation also takes longer as staff are unfamiliar with the results from the Rapid DNA machine.

Table 3: Differences in specs between older and new Rapid DNA sequencers.

Stage of process Number of activities Time taken to complete activity (minutes) Schedule Collection type Notes
Older DNA sequencer machine run   New Rapid 2       1 Fixed – 2880       Fixed – 120 Wednesday @ 0900 Friday @ 1500 Mon-Fri All       8 Can hold up to 100 samples in one run Can hold
DNA sequencer machine run     0900-1700   up to 8 samples in one run
  Validation   1   Uniform(15,20)   Mon-Fri 0800-1500   –  

Scenario 2 – addition of courier to the Rapid DNA process

Scenario 2 is as Scenario 1, except now a courier picks up the samples as they are taken by the CSI (see Figure 2 for process map). To make this work, several things must happen. A courier is on standby during CSI working hours, and the CSI rings the courier up once they have a DNA sample to collect. The courier will make a tour of CSI locations around the day, picking up samples and delivering them back to the lab as soon as is possible.

To facilitate this CSIs are now required to log DNA samples on a networked tablet at the crime scene, rather than back at the station at the end of the day. This adds an average of 15 minutes to each crime scene visit, but means the CSI can stay out longer as they no longer need to come back to the station to log evidence. The changes to the parameter estimates for the Simul8 model are given in Table 4.

Figure 2: Rapid DNA process map with courier transport.

Table 4: Changes to process for courier transport.

Stage of process Number of activities Time taken to complete activity (minutes) Schedule Collection   Notes type
CSI visit   CSIs input 4*   1 Triangular(65,75, 85) Fixed – 60 Mon-Fri 0800-1600 Mon-Fri –   All
evidence into system   minutes 1500-1600  
Courier 1 Uniform(60,120) Mon-Fri All
  Transport to   1   Uniform(60,120) 0800-1600 Mon-Fri   All
lab     Collection @ 1600  

*Due to increase in time taken at crime scene four CSIs are now needed to prevent over-utilisation.

Scenario 3 – 24 hour CSI visits

This scenario is the same as Scenario 2 (see Figure 2), except now CSIs provide 24 hour coverage, 7 days per week. We want to model this because this is an obvious way to speed up the process, where waiting for the CSI visit can be a major bottleneck (especially over the weekend).

The changes to the parameter estimates for the Simul8 model are given in Table 5.

Table 5: Changes to process for 24 hour CSI visits.

Stage of process Number of activities Time taken to complete activity (minutes) Schedule Collection   Notes type
  CSI visit   1*   Triangular(65,75,   24 hours, 7   –
    85) days per  
Courier 1 Uniform(60,120) 24 hours, 7 All
      days per  

* CSI availability is now spread over a much longer time period, so a fair utilisation of CSIs can be met with only one CSI operating at any one time.

Scenario 4 – 24 hour lab

This scenario is the same as Scenario 2 (see Figure 2), except now the lab provides 24 hour coverage, 7 days per week. The CSIs work their traditional Monday to Friday shifts. The changes to the parameter estimates for the Simul8 model are given in Table 6.

Table 6: Changes to process for 24 hour lab.

Stage of process Number of activities Time taken to complete activity (minutes) Schedule Collection type Notes
Samples are prepped 1 Uniform(15,20) 24/7
  New Rapid   1   Fixed – 120   24/7     Can hold
DNA sequencer machine run         up to 8 samples in one run
Validation 1 Uniform(10,20) 24/7  
DNA sequence run through ID database 1 Uniform(1,2) 24/7 2% of samples matched to profile on ID databas e

Scenario 5 – Complete 24 hour operation

This scenario combines Scenarios 3 and 4, so that both the CSI visits and the lab provide 24-hour coverage, 7 days per week.

Text Box: Tasks – Scenario Analysis 6. Modify the current DNA matching process to model Scenarios 1-5. a. Run each scenario model for 500 trials using the Random Number Seed allocated to you by email. 7. Estimate the minimum, average and maximum times in system for each scenario. Produce a table listing these values in minutes, including the low and high 95% ranges. a. Incorrect usage of units and/or missing ranges will attract a zero mark. 8. Run ONE trial of each scenario using the Random Number Seed allocated to you by email. a. Extract out the waiting time distributions for each activity. b. Investigate how the changes in each scenario change the relevant waiting time distributions (for example, how does changing the CSI schedule from Mon-Fri to 24/7 influence the distribution of the time to wait for a CSI to arrive and collect a sample?) c. Therefore explain how each scenario works to reduce the overall time in system by reducing the waiting time distributions. d. Note – don’t just use the average waiting time. Waiting times can be reduced by reducing the time that ALL samples wait, but also by reducing the MAXIMUM time waiting. Averages will not give you enough information to explain this.

Return on Investment (ROI) analysis

The objective of the new Rapid DNA process is to provide evidence to catch criminals faster. However, the move to new machines, networked working and 24 hour processes will incur significant cost increases. In this current age any expenditure must be justified, so you are asked to conduct a ROI analysis to show how the new process may improve matters.

A popular theory of policing is the “golden hour”, where the quicker a suspect can be identified, the greater the chance of successful arrest. Thus, much of the aim of policing is to be present as quickly as possible. This applies to the collection of forensic evidence.

Forensic evidence typically isn’t considered enough to convict a suspect, so in the case of petty crimes such as burglary and theft, investigators want to identify suspects quickly so that they can catch the offender with the stolen goods. A rough rule of thumb is that if a suspect can be identified within 2 days, there is a much better chance of arresting the suspect.

After extracting historical arrest data, you have constructed a reasonable objective function for the probability of arrest, which is shown in Figure 3.

Figure 3: Probability of arrest as a function of days since crime was committed. This is the objective function to be used in the ROI analysis.

You have also estimated the costs associated with each scenario, which are listed in Table 7.

Table 7: Predicted costs per year associated with each scenario modelled

Scenario Cost per year (£m)
Scenario 0 – Current process 5.0
Scenario 1 – Rapid DNA machines only 7.0
Scenario 2 – Rapid DNA + courier 7.5
Scenario 3 – Rapid DNA + courier + 24hr CSI 9.0
Scenario 4 – Rapid DNA + courier + 24hr lab 8.0
Scenario 5 – Rapid DNA + courier + 24hr CSI + 24 hr lab 10.0
Text Box: Tasks – ROI analysis 9. A standard “ROI” metric for policing is arrests per £m spent. Assuming a constant rate of 5000 DNA samples per year, estimate the ROI for the traditional DNA forensics process and the proposed Rapid DNA scenarios. Present your findings in a suitable graph. 10. Discuss the ROI findings. What is your recommendation? Do you recommend moving to a Rapid DNA process? If so, which scenario do you recommend? 11. The ROI is derived from the average time in system. What are the limitations of such an analysis? a. What effect do you think the distribution of the times in system for each scenario (which will largely be driven by the bottlenecks) will have? b. Can you work out another way to assess the ROI in a more realistic manner? Does the distribution alter any of your recommendations? (Note - it is NOT correct to calculate the ROI using the minimum and maximum times in system).


You must provide a written report with your findings and conclusions. You must fully support all answers and conclusions with evidence and appropriate analysis.

The report template should guide you to the appropriate structure. The maximum word count is 1500 (excluding figure/table captions and references). You must follow the APA typesetting style. Where relevant, write in the first person and use the active (rather than passive) voice. The report must logically flow, and your data collection, analysis, results and discussion should be clear, well-supported and concise.

Full marks will be given for i) a clear and concise report that fully explains the reasoning of your analysis and conclusions; ii) a logical chronology from background to the problem through to recommendations to the company, and iii) correctly and consistently-formatted typesetting and figures/tables and iv) being a pleasure to read. More detail is given in the accompanying grade descriptor.

Please also see the style guide.

Model files

You must submit your model files (which includes all Simul8 files and any files associated with calculating the MMc solution to Task 1). All files must be clearly labelled.


All results MUST match the results you present in your report – failure to ensure this is the case will result in substantial reduction in marks.

Simul8 files must be uploaded with results already run (making sure that simulations are run with the random number seed allocated to you by email).