Many companies, even medium-sized and larger firms, still rely on a spreadsheet-based foundation for managing capacity, even if they’ve added other application- and platform-specific tools to the mix. Meanwhile, staffing and processes have, naturally, conformed to fit that collection of tools. While everything might be working well enough for now, it’s only a matter of time before the looming risk of a serious failure becomes a reality. Capacity management functions that rely on spreadsheets are inherently risky, prone to failure and might not comply with today’s regulations. Even if they try to be structured like a database, or have been dressed up like an app using VBS, spreadsheets are flat files and have limitations. Yet the prospect of throwing out years’ worth of processes and investing in an automated capacity management solution can seem overwhelming. Join this webinar to learn a practical approach to transitioning away from manual processes and spreadsheets while adopting automation that is right fit for your organization’s needs. View this webinar with CMG on-demand, where we cover: • Risks and limitations of a spreadsheet-based approach to capacity management • Capacity Management Automation: Options and Advantages • Best practices and real-world examples

1. Just Say No to Spreadsheets
A Practical Approach to Automating
Capacity Management
Presenters:
Dale Feiste – Syncsort Sales Engineering

2. • Top 5 Pitfalls of Spreadsheets
• Options for Automation
• ROI of Automation
• Customer Case Study
• Q&A
Today’s Agenda
2

3. Top 5 Pitfalls of Spreadsheets

4. Top 5 Pitfalls of Spreadsheets
• Design
• Data Quality
• Change Management/Versioning
• Decision Support
• Productivity
4

5. • Functionality limited by spreadsheet coding skills
of the author/owner
• Little/no integration with other applications
• No external validation of approach, assumptions
and formulas/calculations
• No entity relationship documentation
• Difficult to transfer ownership due to unique and
often complex, cross referenced formulas and
structure
5
Pitfall 1: Design

6. • Incomplete/choppy data records due to
periodic, snapshot data ingest
• Error-prone manual data transcription and
reformatting
• High potential for accidental data or formula
corruption
• Limited/no validation of ingested data before
it is used for reporting
6
Pitfall 2: Data Quality

7. • Difficult, time consuming manual
modifications required for every new app or
system added to the environment
• Poor scalability - new infrastructure/
processes require deep structure spreadsheet
re-build
• Limited/no ability to transfer or integrate
processes during mergers, restructuring
7
Pitfall 3: Change Management/
Versioning

8. • Lack of direct and timely access to reports by
business units/stakeholders
• Slow response to special report requests
• Limited/inflexible functionality for trend
analysis and monitoring
• Regulatory compliance audit risk: difficult
validate data gathering and reporting
methodology for compliance reporting
8
Pitfall 4: Decision Support

9. Getting the data
• Extensive reliance upon data source owners/experts
– double-work
• Frequent, time-consuming data gathering cycles via
disparate, app-specific tools
Working with the data
• Manual data transcription and reformatting
• Manual spreadsheet modification/re-builds
Providing insights
• Slow, labor-intensive analysis, modeling
9
Pitfall 5: Productivity

10. Capacity Management
Automation

11. Balance ROI and quality of results
• Automating capacity management is not about replacing people,
but pairing technology with people for optimal return and results
Think about scalability and extensibility
• How will you manage increases in data volumes, extend to
support new applications and platforms
People should focus on functions that
• Require situational awareness
• Need novel problem-solving and judgment
• Are critical to the success of the business
Automation is best suited for functions that
• Require numerical accuracy and precision
• Are high-volume and repetitive
• Enable and accelerate integration of systems, and the delivery of
analysis and graphical reporting11
Considerations for Automation

12. Data Gathering
• Connectivity to, and continuous collection of, all systems and alerting
data – from mainframe, physical, virtual and cloud-hosted systems –
and storage in unified repository.
• Delivers more complete, accurate data, without dependency on
expertise in the source systems.
Data Formatting
• Efficient, timely access to transformed capacity data – without
requiring manual modification or intervention.
• Increases operational efficiency and reduces the complexity of manual
manipulation.
Reporting
• Automated reporting and analysis, with the ability to design and
modify reports quickly.
• Provides consistent, reliable insights to the business on-demand.
Opportunities to Automate
12

13. Trend Analysis and Modeling
• Automate highly sophisticated, numerical calculations for
analysis and modeling, performed on more comprehensive
data sets.
• Easy-to-repeat and -share capacity analysis enables decision-
making based on complete, current and comprehensive data
Opportunities to Automate
13

14. ROI of Automation

15. Reduced Risk
• Avoiding outages and performance degradation with faster identification
of potential issues and problem resolution
• Meet regulatory compliance audits
Optimized Workloads and Reduced Expense
• Handle higher volume of work by having the right level of computing
resources – hardware purchase deferrals, reduced software costs
Accurate Reporting
• Having the right information in the hands of the right people at the right
time yields better decisions
Improved Productivity
• Less double-work and re-work; skilled staff spends time on value-
generating activities
Automated Capacity
Management ROI
15

16. Customer Case Study

17. 17
Elevate Capacity Management:
• Automates data capture, collection and
storage, as well as report creation
• Supported all key systems – spanning various
versions of Unix, VMware and mainframe
• Scalable to meet increasing data volumes
Syncsort Customer Case Study: Financial Services
Challenge Solution
Impact
Ensure enough processing power to meet 11 sec
SLA for processing loan application and
responding to clients:
• No formal capacity management function
• No software to automate the capture,
reporting and storage of data across key
performance and capacity systems
• Supports rapidly-growing business, while still meeting 11-second SLA
• Faster investigation and resolution of incidents involving performance and capacity
• Right-sized hardware, software and other infrastructure purchases with the ability to balance
resources with the ability to deliver on the 11-second SLA

18. Q & A