Hvordan sikres (mere) værdi af Business Intelligence projekter? JORGEN.STEINES@PLATON.NET 1 WWW.PLATON.NET
Platon The Company A leading Independent Information Management consulting company Headquarters in Copenhagen, Denmark 220+ employees in 9 offices 300+ clients in 8 countries Founded in 1999 Employee-owned company Platon received good feedback in our satisfaction survey. Clients cited the following strengths: experience and skill of consultants, business focus and the ability to remain focused on the needs of the client, and a strong methodological approach Gartner July 2008
Nordens største Information Management konference: Keynote: 28 unikke præsentationer, bl.a: Fokus på Business Intelligence og Master Data Management Unikke internationale eksperter Netværksreception med underholdning af Jonatan Spang Afsluttende netværksmiddag Vi glæder os til at se dig og dine kollegaer d. 12. oktober 2011. Book allerede datoen i din kalender i dag! Du kan følge udviklingen af programmet på www.im2011.net. JAMES TAYLOR Vi er stolte over at annoncere årets keynote-taler: én af de største Business Intelligence-guruer hele vejen fra San Francisco i USA. James er en ledende ekspert og forfatter indenfor regelbaseret beslutningsstøtte (Decision Management & Predective Analytics) og en anderkendt keynote-taler ved diverse globale konferencer. Side 3
Agenda What is BI BI Governance BI Adoption BI requirement specification Summing up 4
Data Warehouse & Business Intelligence Data Warehouse Data Mining OLAP The term Business Intelligence (BI) covers the use of information to drive business insight. Basically it s about providing a better foundation for decision makers by providing information in the right form, in the right Enterprise quality, at the right time. reporting Analytical applications The term Data Warehouse covers?!? the management of data Data is extracted from operational systems and integrated in the Data Warehouse environment Business order to provide Intelligence an enterprise wide perspective, one version of the truth. Page 5
Drivers for Business Intelligence The Multidimensional Manager: 24 Ways to Impact your Bottom Line in 90 days CEO Low profitability Decreasing market share Slow reaction to threats and opportunities Challenges implementing business strategy Challenges with mergers... Finance Cash flow problems Low profitability Losses on debts receivable Inflexible planning process CPM aspirations... IT Heterogeneous infrastructure Data quality issues Reporting back-log Project delivery issues... Marketing Decreasing market share Missing cross/up-sales Bad campaign response Slow time to market CRM aspirations... HR Many types of employees High employee turnover Bad employee satisfaction Decreasing competencies Need for collaboration... Procurement Production and logistics Sales Service Unattractive prices Bad service levels Lack of supplier insight Lack of market insight Rising stock levels... Quality issues Falling service levels Increasing lead time Rising inventory levels Resource bottlenecks Increasing distribution costs Inefficient processes Extended value chain aspirations Process outsourcing Just-in-time aspirations... Falling revenue Missing cross/up sales Increasing COGS Missed opportunities Bad forecasting Decreasing prices Complex markets... Bad customer satisfaction Increasing response time More complaints Random service levels... Page 6
An example Page 7
Predictive analytics Codan - Fraud It is estimated that 10% of all insurance claims are attempts to fraud For Codan this equals 400 mill. DKR per year Insurance claim - collect information?? Risk of fraud is predicted through a data mining tool Insurance claim - collect information Standard case Loss consultant investigates Standard case Loss consultant investigates Page 8
Predictive analytics Codan - Pricing Old model postal codes New model 100 x 100 meter cells High risk Low risk Several parameters to determine the risk Only a few from the customer The rest is based on data Page 9
Agenda What is BI BI Governance BI Adoption BI requirement specification Summing up 10
IT Governance Governance Corporate governance IT Governance: Specifying the decision rights and accountability framework to encourage desirable behavior in the use of IT The opposite of Governance: Anarchy (from Greek: ἀναρχίᾱ anarchíā, "without ruler ) "No rulership or enforced authority. "Absence or non-recognition of authority and order in any given sphere. "Act[ing] without waiting for instructions or official permission... The root of anarchism is the single impulse to do it yourself: everything else follows from this. 11
BI Governance BI Governance is the framework and processes for determining the priorities, deployment practices, and business value of enterprise business intelligence initiatives. Who decides what to work on next? How do we resolve conflicting interests? How do we get executive level awareness and support? How do we quantify and track the values of our BI investments? How can we be more proactive and anticipate changing business needs? 12
BI Governance - Business and IT standpoints IT DW BICC Business Business unit Business unit unit DBA Develop ETL Data modelling Requirement Specs Design Front end Standards for reporting User support Develop reports Analyze information Train Users Recommend Actions Execute Bus. Proc. Operational efficiency IT Cost effectiveness Reliability Scalability Flexibility Responsiveness Business Innovation 13
BI Governance - Organisational structure Program Board Program level BICC Coordinate & prioritize Operation level DW Coordinate & prioritize Steering Committee Project A Project level Steering Committee Project B Steering Committee Project C 14
Governance relationships The purist would claim they are independent IT Governance Infrastructure and operational applications Data Governance Information quality and processes BI Governance Business performance and decision support Page 15
Governance relationships IT Governance Infrastructure and operational applications Business strategy alignment Project portfolio management Business value tracking Legal compliance Knowledge management Service Level Agreements Information quality and processes Business performance and decision support Data Governance BI Governance Page 16
Step 1: Define the governance level of the BI Program Step 1: Define the governance level of the BI Program Step 2: Identify decision making bodies Step 3: Define decision areas and decision rights Step 4: Design and implement governance processes Ad hoc Degree of federation BI Project prioritization BI Architectures BI Organisation BI Methodology BI Policies BI Tools & Systems Common Data Definitions One way 17
Agenda What is BI BI Governance BI Adoption BI requirement specification Summing up 18
What can drive better deployment and adoption Strategy clarification Other Focus on usage Better BI adoption Communication, marketing and branding Organisational Change Management 19
Change Management I can not live without my Excel sheets. The successful companies focuses 70 % of the implementation resources on processes, education and other soft aspects and only 30 % on technology Similar to ERP implementations? I need my own definitions. I don t want my results to be visible for all. The users We earn money anyway. Let s build it and they will come. We know what they need. The managers The BI people Page 20
Communication, marketing and branding Branding Provides a single identity when communicating about your BI Program Differentiates your product from other choices Create a logo Use it on reports, the intranet and all communications like newsletters, status reports, presentations etc. Extend your brand through report certification A process of promoting a report to a mass audience Further drives the data integrity of your BI program and builds user confidence Creates a adoption effect as management only wants to view reports that have been branded and/or certified Page 21
Agenda What is BI BI Governance BI Adoption BI requirement specification Summing up 22
Does this look familiar? Increasing costs to fix defects discovered later due to incorrect requirements Analysis Design Development Implementation 23
BI solution types Ad hoc analytics / OLAP Dashboards / cockpits Balanced scorecard Predictive analytics / data mining Performance management Reporting GIS and other visualization Alerts and exception Analytical CRM 24
Types of (BI) requirements Business requirements Information requirements What is the business need, pain or problem? What business questions do we need to answer? What data is necessary to answer those questions? Functional requirements Detailed report / usage requirements How do we need to use the resulting information to answer those questions? Other requirements Detailed layout etc All the other stuff AKA non functional requirements How about defining the business processes that apply the new information to managerial actions? 25
Design inspiration David McCandless: The beauty of data visualization
The requirement specification document The simple version Introduction Business requirements Business process requirements Information requirements Functional requirements Detailed report / usage req. Other requirements 27
The requirement specification document The really simple version 28
The requirement specification document The expanded version Executive summary Introduction Business requirements Business process requirements Information requirements Functional requirements Detailed report / usage req. Security requirements Performance requirements Operational requirements Migration requirements User doc. and training requirements Other requirements http://www.volere.co.uk/template.htm 29
Business process requirements Change is the keyword Textual description is ok Or use a swim lane design where the workflow or supporting instructions, procedures or use cases are changed Procedure Prioritize order based on customer rating by Use Case When the sales rep enters The system shows 30
Cover all information requirements Ask, ask, ask Explain and exemplify - with all stakeholders Facts Business rules Dimensions and hierarchies Value sets Timeliness History How fresh should the data be (update frequency) Specific dates the new data is needed How much calendar time should be covered How about changes in hierarchies - program requirement could be type 2 SCD and project requirement could be type 1 SCD 31
Does this look familiar? Perhaps some more structured techniques are needed? 32
The process & methods The sub activities for specification process is outlined in the figure below. Identify stakeholders Clarify method of collecting requirements Plan and invite for meetings Prepare and send material or mindset at meeting Conduct / collect Consolidate / document Validate/ prioritize Update requirement spec. Send for review Verify and sign off 33
The process & methods Identify stakeholders Clarify method of collecting requirements Plan and invite for meetings Prepare and send material or mindset at meeting Conduct / collect 34
BI and Agile development
The effect of initial roll-out times on project success 36
BI Requirements - Business and IT standpoints Accuracy User Experience Speed Reliability Correctness Scalability Flexibility BICC? Innovation Ease of use 37
Pay attention to data quality Poor data quality is the second most common reason for BI failure Data quality is a big risk Get a clear picture on data quality issues as early as possible - during analysis or even before Don t wait until the development takes place 38
Agenda What is BI BI Governance BI Adoption BI requirement specification Summing up 39
Summing up Value comes from decisions and changed behavior not from providing reports Information requirements are key in all BI projects Make the right balance between time and perfection Expect change and expect to manage change 40