Skills application
Instruction and application
In ProgressML use case proposals and competitor benchmarking
How will these skills help you and your business?
Activity instructions
Choose a business function
Select one of the following industries/business units that best fits the industry you work in.
Industries and business units-Marketing: Promotes products/services, drives brand awareness and generates leads.
Sales:
Converts leads into customers, manages relationships and drives revenue.
Operations:
Oversees production, logistics and process efficiency to ensure smooth workflows.
Human resources (HR):
Manages recruitment, employee development, compliance and workplace culture.
Finance and accounting:
Handles budgeting, financial planning, risk management and compliance.
Customer service:
Supports customers, handles inquiries and ensures satisfaction and retention.
IT and security:
Manages infrastructure, cybersecurity and tech solutions to support business operations.
Product development:
Designs, tests and enhances products/services to meet customer needs.
Supply chain and procurement:
Manages sourcing, supplier relationships, logistics and inventory.
Legal and compliance:
Ensures the company adheres to laws, regulations and industry standards.
Brainstorm ML use cases
Imagine you’ve been tasked with improving business performance for your chosen business unit. Brainstorm at least two potential ideas to use ML to drive improved performance.
If you're working on a business unit that you're not familiar with, you can see some typical key performance indicators (KPIs) for your choice of business unit below.
Marketing KPIs-Customer acquisition cost (CAC) – total cost of acquiring a new customer.
Marketing qualified leads (MQLs)
– number of leads that meet predefined marketing criteria.
Return on marketing investment (ROMI)
– revenue generated from marketing efforts compared to spend.
Website traffic and conversion rate
– number of visitors and percentage converting to leads/customers.
Brand awareness and engagement
– social media reach, impressions and engagement rates.Sales KPIs-Sales conversion rate – percentage of leads that convert into paying customers.
Average deal size
– the average revenue per closed deal.
Sales cycle length
– average time taken to close a deal from lead to customer.
Quota attainment
– percentage of sales team members hitting their targets.
Customer lifetime value (CLV)
– total projected revenue from a single customer over time.Operations KPIs-Process efficiency ratio – measures productivity vs operational costs.
Order fulfilment time
– average time taken to complete and deliver an order.
Operational cost per unit
– cost of producing/delivering a single unit of product/service.
Downtime and utilisation rate
– percentage of time equipment or resources are operational.
First-time right rate
– percentage of processes completed without errors or rework.HR KPIs-Employee turnover rate – percentage of employees leaving within a given period.
Time to hire
– average time taken to fill open positions.
Employee engagement score
– satisfaction and engagement levels from surveys.
Training and development completion rate
– percentage of employees completing training programmes.
Absenteeism rate
– percentage of working days lost due to employee absence.Finance and accounting KPIs-Net profit margin – percentage of revenue remaining as profit after expenses.
Cash flow ratio
– measures the company’s ability to cover its short-term liabilities.
Accounts receivable turnover
– how quickly outstanding invoices are collected.
Return on assets (ROA)
– profitability relative to total company assets.
Budget variance
– difference between projected and actual budget performance.Customer service KPIs-Customer satisfaction score (CSAT) – measures customer happiness with support interactions.
First response time (FRT)
– average time taken to respond to customer enquiries.
First contact resolution (FCR)
– percentage of issues resolved in the first interaction.
Net promoter score (NPS)
– measures customer willingness to recommend the company.
Ticket volume and resolution time
– number of support tickets and average resolution time.IT and security KPIs-System uptime percentage – availability of IT infrastructure and systems.
Mean time to resolution (MTTR)
– average time taken to resolve IT issues.
Security incident response time
– speed of addressing cybersecurity threats.
IT cost per employee
– cost of IT services and tools per employee.
Compliance audit pass rate
– percentage of security and regulatory audits passed.Product development KPIs-Time to market (TTM) – duration from product ideation to launch.
Product defect rate
– percentage of faulty or rejected products.
Innovation pipeline strength
– number of new products/features in development.
Customer feedback and adoption rate
– usage and satisfaction with new features/products.
Research and development (R&D) ROI
– revenue generated from R&D investments.Supply chain and procurement KPIs-On-time delivery rate – percentage of orders delivered on schedule.
Supplier performance score
– evaluates supplier quality and reliability.
Inventory turnover ratio
– frequency at which inventory is sold and replaced.
Cost per order
– total cost associated with fulfilling an order.
Logistics efficiency
– measures transport and warehouse optimisation.Legal and compliance KPIs-Regulatory compliance rate – percentage of compliance with legal requirements.
Contract cycle time
– average time taken to review and finalise contracts.
Legal risk exposure
– number of legal disputes and associated risks.
Data protection and privacy compliance
– adherence to data security regulations.
Audit success rate
– percentage of successful legal and compliance audits.
Research competitors
Research known competitors or industry leaders that are using ML to solve their challenges within your chosen industry or business unit.
Tips for conducting researchBy researching a range of these sources, you can uncover what’s working, what’s evolving and where opportunities may exist to innovate in your own business.
Industry reports and case studies:
Look for reports from trusted sources such asGartner, McKinsey, Deloitte and Harvard Business Review that analyse ML trends and real-world applications.
Competitor websites and blogs:
Check the AI/technology sections of competitor websites, product pages and company blogs for insights into their ML initiatives.
Tech and business news:
Follow publications likeTechCrunch, Wired, Forbes and MIT Technology Review for updates on how companies adopt ML.
LinkedIn and company announcements:
Search for posts, white papers or press releases from industry leaders showcasing ML-driven innovations.
Patents and research papers:
Google Patents and platforms likearXiv.org can reveal ML breakthroughs competitors are working on.
AI vendor case studies:
Explore ML service providers (e.g. AWS, Google Cloud, Microsoft AI) as they often publish case studies featuring real business applications.
Webinars and conferences:
Attend AI/ML-focused events or webinars where companies share best practices and success stories.
Create a new and innovative ML use case
Combine your use cases with competitor insights to refine your best ideas to stand out in the market. Use the insights gained in task 3 to refine and improve your ideas. The aim for this task is to create a new and innovative ML use case that will help your business stand out in the marketplace.
Group presentations
Each group will have two to three minutes to share:
- Your top ML use cases.
- Key learnings from the competitor’s approach.
- Improvement or replication ideas. During the presentations, the observing teams may ask questions and make suggestions to further improve the use case.
Key takeaways
- Brainstorming ideas and then benchmarking competitors' ML use cases can help you refine and improve your solutions.
- Benchmarking competitor use cases is a continuous process that will help develop a broader understanding of ML capability.