The document discusses Waterstons' roadmap for business intelligence (BI) and analytics, highlighting the importance of understanding and maximizing the value of business data. It outlines the evolution from operational reporting to advanced business analytics and predictive analytics, emphasizing iterative approaches that align with business needs. Additionally, the document touches on future trends like automation and the concept of a 'self-healing' business.

1. @Waterstonsltd
www.waterstons.com
BI: Beyond Intelligence
Introducing Business Insight Maturity
Dan Burrows, Chris Hatton, Michael Nesbit

2. Agenda
@ Introduction
@ Some data about data
@ Waterstons’ BI roadmap
@ BI, BA and CPM - Where have we been?
@ Where are we going next?

3. Introduction
@ The three MISketeers
@ Waterstons and business analytics
@ Our journey to enlightenment

4. Some data,
about data

5. What does this mean to me?
@ Largely, probably nothing
@ Most businesses don’t care about Facebook, Instagram, Twitter, etc
@ It’s hard enough interpreting your own data, let alone anyone else’s
@ Maximising the value of your business information is vital
@ Once you understand what you already have you can worry about the rest

6. Understanding Your Data’s Value
@ Many businesses fail to capitalise on the value of their data
@ Predefined reports are useful, but the real value comes from the insights
hidden in an organisation’s data.
@ Business analytics is not all about answering questions
@ It’s about establishing the most insightful lines of enquiry
@ And supporting decisions with facts, trends and predictions
@ Shocking fact: few businesses are really good at using their data

7. Waterstons’ BI roadmap
@ An approach to delivering an analytics project
@ A series of delivery actions in a theoretical progression
@ A cradle to grave process for embedding, designing and developing
intelligence

8. The Utopian Process
Approach Ramp
•Selling BI as a concept
•Understanding the need, problems and solutions
Business
Background
•Understanding the business strategy, drivers, reporting requirements and KPIs.
•Decision Point
Conceptual
Design
•Understanding KPI definitions and data sources required
•Defining the data warehouse contents
Readiness and
Approach
•Analysis of systems and data availability, approach and technology selection
•Break-out Point – gap analyses, system implementation, consolidation
Functional
Design
•Reports, visualisations, dashboards
•User-group specific requirements
Build
•Build the data warehouse and ETL routines, implement chosen BI tools, develop and deploy visualisations

9. Waterstons’ BI roadmap
@ Not necessarily a linear progression; focus on business needs
@ Iteration reflects real business
@ Project experience demonstrates a different story

10. BI in the “Real World”
Approach
Ramp
Business
Background
Conceptual
Design
Readiness
and
Approach
Functional
Design
Build

11. Time for a change
@ Analysis of business data has moved on significantly
@ New analytics tools and discovery products are available
@ The popularity of, and desire for instant analysis has exploded
@ A new roadmap for delivering insight to our customers was needed

12. 18 reasons in one simple slide

13. Where did you come from?
@ In the beginning, there was the operational report. With it came
answers to questions.
@ What am I making today?
@ Who should be at work making it?
@ Are all the parts in stock?
@ What orders am I supposed to dispatch?
@ Snapshot answers to questions – focussed on activity

14. Stage 1: Monitor
Operational Reporting
• What happened, when and where?
• Manual process
• Transactional
• Line-of-Business systems

15. Operational Reporting
@ Traditional reporting scenarios
@ Real Time
@ Detail
@ Line of business management and staff
@ Operational dashboards
@ Manage intra-daily business processes (low-latency)
@ Legislative reporting requirements
@ Traditional reporting technology is still relevant in an analytics context
@ Frozen historic snapshot
@ Controlled or limited access to interactive analytic features
@ Specific or specialised requirements for data visualisation

16. Where did you go?
@ Operational reporting was good. But not good enough. Enter the
world of Business Intelligence.
@ What has my performance been vs. KPI target?
@ How does our performance compare with last year?
@ Am I making enough things/enough margin?
@ Are the decisions I made last week/month/year making a difference?
@ Temporally related questions and answers – focussed on results

17. Stage 2: Question and Control
Business Intelligence
• What can I do about it?
• Consistent data sources
• Scorecards and dashboards
• Metrics-based

18. Business Intelligence
@ Operational Reporting
@ Data Warehouse
@ Multiple Data sources
@ One version of the truth
@ Defined KPIs
@ Targets
@ Last Year
@ Actuals
@ Historical Trends
@ Accumulation of Data

19. What’s current?*
@ Knowing what’s been going on gives way to working out what to do
next. The Business Analysis train arrives.
@ Hmm, I wonder what happened to cause that spike in sales?
@ Do blue ones REALLY work better than the red ones?
@ Are we attracting the most profitable customer groups?
@ Why, why, why?
@ Interrogation to answer ad-hoc questions – focussed on insight
*This slide formerly entitled “Where did you come from, Cotton Eyed Joe?”

20. Business Analytics
Business Analytics
• What’s happening now and why?
• Enterprise level data
• Self-service data
• Insight-based

21. Business Analytics
@ Operational and BI reporting
@ Analysis of reporting to ask questions
@ Why trend occurs?
@ What can be done to change trend?
@ Power users performing analysis
@ Ad-hoc reports
@ Interactive drill down / slice and dice
@ Potentially discover new trends

22. Where are you going now?
@ What’s leading edge? Data driven forecasting, strategy and planning.
The world of Predictive Analytics is growing.
@ What will next year look like?
@ What would happen if we lost that customer?
@ Could we cope if a competitor entered the market?
@ Could we satisfy demand if the number of customers doubled?
@ Trend analysis answering ‘what-if’ questions – focussed on the future

23. Stage 4: Beyond Intelligence
Predictive Analytics
• What’s going to happen?
• What-if analysis
• Strategic integration
• Business forecasts and planning

24. Predictive Analytics
@ What-if scenario modelling
@ Manufacturing; forecasting and promotion planning
@ Workflow
@ Predictive
@ Tools for extrapolation of trends
@ Recognition of trends; automatic analysis of data
@ Data mining algorithms:
@ Compute a trend for sales data
@ What characteristics make a good customer
@ How likely a student is to drop out

25. Beyond Intelligence
Operational Reporting
• What happened, when
and where?
• Manual process
• Transactional
• Line-of-Business
systems
Business
Intelligence
• What can I
do about it?
• Consistent
data sources
• Scorecards
and
dashboards
• Metrics-
based
Business
Analytics
• What’s
happening
now and
why?
• Enterprise
level data
• Self-service
data
• Insight-
based
Predictive
Analytics
• What’s going
to happen?
• What-if
analysis
• Strategic
integration
• Business
forecasts
and
planning

26. Is there life after intelligence?
@ Predictive analytics is not the end
@ As scary as it may seem, there is a Stage 5
@ Automated control methods already exist
@ Extended automation will change decision making processes
@ The ‘self-healing’ business could become a reality
@ Dependent entirely on the risk-appetite of the business
@ Not for the faint hearted!

27. Any questions?
dan.burrows@waterstons.com
chris.hatton@waterstons.com
michael.nesbit@waterstons.com
http://www.waterstons.com
@WaterstonsLtd
@DanThe7s

28. Next seminars
@ Mobile Device Management and BYOD – The major players
@ Wednesday 25th June, London Office
@ The Magical Project Manager
@ Friday 4th July, Durham Office
@ Sign up online via www.waterstons.com