1. What might be some reasons for the theft in this scenario that training alone did not
address?
Answer 1In this case, systemic and environmental factors—rather than ignorance—are probably
the cause of theft. Theft can be made easier by inadequate internal controls, such as
inadequate supervision or bad financial reconciliation. Workers may be more likely to
act dishonestly if they are experiencing financial strain or are subjected to high
performance and sales targets. Additionally, training is less successful due to cultural
variables including worker cooperation, a lack of responsibility, or a fear of reporting
misconduct. Training ignores the underlying behavioural, organizational, and structural
problems at hand since it concentrates on knowledge and compliance.
2. How would you identify key data points to analyze this problem using people
analytics?
Answer 2
It is essential to find information that connects people, processes, and outcomes in
order to evaluate theft successfully. Cash reconciliation logs would be used to spot
discrepancies, transaction records would be used to keep an eye on odd activity like
recurring refunds or voids, and employee shift data would be used to determine who
was on duty during occurrences. CCTV time stamps and access records can also be
used to verify odd activity. HR-related data, such as length of service or prior disciplinary
history, may reveal whether theft is linked to particular employee characteristics. When
taken as a whole, these data points provide a more thorough understanding of patterns
and their causes.
3. If you were on the people analytics team, what types of data would you collect to
understand the theft patterns better?
Ans3
I would gather operational and labour data as a member of the analytics team to look
into theft trends. Using operational data, such as transaction logs, cash register
balances, and exception reports, would make it simpler to identify discrepancies in cash
management. Employee schedules, training logs, and previous disciplinary actions can
all provide insight into whether theft occurs during specific shifts or involves particular
individuals. Using access logs and surveillance timestamps from security data, we could
verify any discrepancies.
4. What tools and techniques would you use to analyze this data?
Ans 4
In order to understand the data collected, I would use a variety of analytical techniques
and resources. Showing branch hotspots, time-of-day trends, and individual employee
abnormalities can be aided by tools like Tableau or Power BI. Variance and correlation
analysis are two statistical methods that would demonstrate relationships between theft
and specific variables like shift length or overtime hours.
1) Reasons for stealing besides education
Your response is excellent; you highlighted factors that are realistic, such as culture,
inadequate oversight, pressure, and weak controls. I especially like that you brought up
company culture because it's often overlooked when theft occurs. Although you could
elaborate by mentioning employee collaboration or ineffectual deterrents (such
inadequate CCTV coverage), your response generally successfully tackles the primary
concerns.
2) Identifying crucial data components
You did a great job spotting teller shifts, overtime, cash inconsistencies, and access
logs—these are the exact kinds of information that connect people's actions to
outcomes. Since audit results offer official verification of control weaknesses, I
appreciate that you included these as well. You may add exceptional transactions, such
refunds and voids, which are frequently interpreted as theft signals, to strengthen your
response even further.
3) Data collection for patterns
Because it includes both HR (schedules, tenure) and operational (transactions,
overrides) data, your list is strong. This balance shows that you're taking into account
both people and processes, which is crucial for people analytics. CCTV timestamps and
door access logs are examples of possible inclusions since they provide tangible
evidence to back up transaction records. Otherwise, the right points are already linked
in your response.
4) Techniques and tools
This is a very helpful strategy using dashboards, trend analysis, and simple statistics
makes sense, especially as a first step. Since it is essential to anomaly detection, I
appreciate your emphasis on spotting odd activity. You could go farther by using
clustering or anomaly detection models for a more thorough examination, but your
response currently provides a straightforward and useful approach.
Monday- Available full day Tuesday- After 11 am Wednesday- After 3 pm ThrusdayAfter 3 pm Friday- After 11 am Saturday- Available full day Sunday- Available full day
Hiring Metrics & How They Prove Value for Money
1. Number of Hires
o
What it shows: How many people were successfully recruited in a set
time.
o
Value for money: When paired with total recruitment spending, you get
Cost per Hire. A lower cost per hire means resources are being used
efficiently.
2. Source of Hire
o
What it shows: Which recruiting channels (referrals, job boards,
agencies, LinkedIn, etc.) bring in candidates.
o
Value for money: Helps identify the most cost-effective channels. If
referrals bring in great talent at lower cost, you can prove that money isn’t
being wasted on less effective sources.
3. Failed Hires (New Hire Turnover)
o
What it shows: % of hires who leave within the first year.
o
Value for money: A low failed-hire rate means recruitment and
onboarding are effective, so hiring money is well spent. A high rate means
wasted investment, showing where costs must be reduced.
4. Employee Performance (Quality of Hire)
o
What it shows: How well new hires perform (via reviews, feedback,
productivity).
o
Value for money: If new hires are high performers, the business gains
more than it spends to hire them — a clear ROI.
5. Retention Rate (of New Hires)
o
What it shows: % of employees who stay long-term.
o
Value for money: The longer employees stay, the more the company
recoups its hiring investment (recruitment + onboarding + training costs).
High retention = stronger ROI.
6. Build vs Buy Rate
o
What it shows: % of positions filled internally (promotions, transfers) vs
externally (new hires).
o
Value for money: Internal hires (“build”) are usually cheaper and quicker
than external hires (“buy”). Tracking this shows whether external hiring
costs are justified when internal options aren’t available.
7. Labor Costs
o
What it shows: Total cost of employees (salaries, benefits, bonuses, etc.).
o
Value for money: Shows the true cost per employee. By comparing this
to productivity or revenue generated, you can prove whether hiring adds
financial value to the company.