May 1, 2014
Effective Cost Transparency from
Imperfect Data
Todd Tucker – TBM Council/Apptio
Kevin Teets – Apptio
Deb Krue...
© 2014 Apptio, All rights reserved.1
© 2014 Apptio, All rights reserved.2
The Importance of Why
© 2014 Apptio, All rights reserved.3
“Why” Questions in IT?
Why do we need so much
tier 1 storage?
© 2014 Apptio, All rights reserved.4
Business Capabilities
Business Services
Technology
Services
Application Services
Plat...
© 2014 Apptio, All rights reserved.5
IT Cost Transparency is not about
What does IT cost? It’s about…
WHY does IT cost wha...
Transparency Every Business Needs For Fact-Based Decisions
© 2014 Apptio, All rights reserved6
“We knew more visibility wo...
What Questions Can You Answer with Transparency?
A P P L I C A T I O N S A N D S E R V I C E S B U S I N E S S U N I T S
...
Where and When Would Better Cost Transparency Have An
Impact For You?
© 2014 Apptio, All rights reserved8
 Questions from...
© 2014 Apptio, All rights reserved.9
The Business Value of Transparency
Clorox Co. has promoted CIO Ralph Loura
to senior ...
© 2014 Apptio, All rights reserved.10
What Does This Have to Do with Data?
Plan CapEx/OpEx Run/Grow/Transform Fixed/Variable Location/Regions Month/Quarter/Year
Cost Centers Accounts
General Ledger...
Data and Allocation Methods (Example)
© 2014 Apptio, All rights reserved12
Hardware Software Internal Labor External Labor...
Challenges of Creating Cost Transparency
TRIGGERS
 Month end close
 Forecasts
 Project financial
 QBRs
 Ad hoc questi...
© 2014 Apptio, All rights reserved.14
Which Comes First: Transparency or Good Data?
“There's no better way to
focus and pr...
May 1, 2014
Cost Transparency at
State of Iowa
© 2014 Apptio, All rights reserved.16
Mission: Provide Iowans unified, comprehensive, value-driven
administrative services...
May 1, 2014
Working with Imperfect Data
© 2014 Apptio, All rights reserved.18
Introduction
1. TBM ADVISORS –
MISSION STATEMENT
2. WHY AM I TALKING
ABOUT DATA QUAL...
© 2014 Apptio, All rights reserved.19
Challenges
Don’t want to start TBM
because of poor data quality
Do not have confiden...
© 2014 Apptio, All rights reserved.20
Apptio Data Quality Dimensions – Defined
MAINTAINABILITY
A measure of the degree to ...
© 2014 Apptio, All rights reserved.21
Data Quality Ecosystem
Data Governance
Ownership (TBMO)
Data Advisor
Data Sources
Da...
© 2014 Apptio, All rights reserved.22
Data Governance Organizational Model
OFFICE OF THE CIO
Executive
Sponsorship
Busines...
© 2014 Apptio, All rights reserved.23
Data Advisor
Data Advisor defines the
data that you need to
build out each
component...
© 2014 Apptio, All rights reserved.24
Data Quality Integration into Change Management
Change
Management
• Maintainability
...
© 2014 Apptio, All rights reserved.25
Apptio Adaptive Data Management
DISPARATE RAW DATA
• Data checks
• Parse, filter
• D...
© 2014 Apptio, All rights reserved.26
Data Mapper
Data Advisor Master
Data fields that
support our Out of
the Box content
...
© 2014 Apptio, All rights reserved.27
Data Foundations
Data Strategy
Data Governance
Source Systems
Data Quality Dimension...
© 2014 Apptio, All rights reserved.28
Data Quality Workflow
© 2014 Apptio, All rights reserved.29
Data Quality Dimensions – Dashboard
Drill into
any KPI for
additional
detail
© 2014 Apptio, All rights reserved.30
Data Quality Dimensions – Maintainability
Answer 3
questions
to evaluate
score
© 2014 Apptio, All rights reserved.31
Data Quality Dimensions – Uniqueness
Total number of
duplicate records
© 2014 Apptio, All rights reserved.32
Data Quality Dimensions – Completeness
# blanks
per column
© 2014 Apptio, All rights reserved.33
Data Quality Dimensions – Completeness
Slice into
each column
to discover the
rows c...
© 2014 Apptio, All rights reserved.34
Data Quality Dimensions – Validity
First –
configure
Settings
Invalid cells
are base...
© 2014 Apptio, All rights reserved.35
Data Quality Dimensions – Validity Settings
Instructions
Values that
are new and
hav...
© 2014 Apptio, All rights reserved.36
Data Quality Dimensions – Validity Settings
Assign “Valid”
or “Invalid”
as appropria...
© 2014 Apptio, All rights reserved.37
Data Quality Dimensions – Validity
# Invalid
values per
column
Compare
against
expec...
© 2014 Apptio, All rights reserved.38
Data Quality Dimensions – Frequency Distribution
Instructions
and overview
of calcul...
© 2014 Apptio, All rights reserved.39
Data Quality Dimensions – Frequency Distribution
Review
Threshold
Row number
Set
Thr...
© 2014 Apptio, All rights reserved.40
Data Quality Dimensions – Frequency Distribution
Adjust slicer
settings and
insert T...
© 2014 Apptio, All rights reserved.41
Data Quality Maturity
May 1, 2014
Data Quality Journey at
The State of Iowa
© 2014 Apptio, All rights reserved.43
 Data comes from many different and varied systems
 HRIS, general ledger system, M...
© 2014 Apptio, All rights reserved.44
 Explained that financial data isn't 'perfect' and gets better with
everyone's help...
© 2014 Apptio, All rights reserved.45
 Semi-annual inventory of servers, ports, racks
 Ease the burden of reporting in l...
May 1, 2014
Building Trust in Our Data
© 2014 Apptio, All rights reserved.47
Steps to Improve Trust in the Data
 Beta test new models or major
changes
 Be tran...
May 1, 2014
Where To Learn More
© 2014 Apptio, All rights reserved.49
Apptio Resource Center
Top 5 Reasons for Avoiding IT Cost Transparency
(May 6 Webcas...
© 2014 Apptio, All rights reserved.50
TBM Council
 TBM Conference in Miami
 Workgroups
 CXO peer groups for vertical
in...
TBM Conf 2014 Miami – fountain blue
2014
Miami
TBMconference.org
October 28-30
52
Thank You!
Todd Tucker
TTucker@TBMcouncil.org
Kevin Teets
KTeets@Apptio.com
Info@Apptio.com
Apptio.com
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Presentation from State of Iowa's Cost Transparency Journey at ITFM Week 2014

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IT Cost Transparency is not about what does IT cost? It’s about why does IT cost what it does and how can they use their money and other resources to create more value.

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  • Most companies take it for granted that they know what it costs to run their business. They track the cost of running key disciplines like R&D, manufacturing sales and marketing. They track the cost of providing their key products and services. They track who their customers are and how much they are buying. And they make decisions every year, every quarter, every month, and every day based on this shared understanding. If they didn’t have these essential facts, how long would it take to make a decision on whether to invest in a new product or discontinue it, close down a factory or build a new one?Whether or not you think of your IT organization as a business in its own right, the same principles apply. What we’ve seen in working with hundreds of IT leadership teams like yours is that there are essential views they all need to drive the right decisions and make them quickly.
  • We’ve found there are key moments of truth where better cost information makes an impact for IT organizations, and these are some of the patterns we see. One of our goals of this meeting is to better understand where you could use
  • Big changes beyond IT’s control are putting transparency and accelerated decision-making on the front burner for more and more companiesFor example,(New competition): Cloud providers are marketing directly to the business, and what the business sees isn’t usually a fair apples to apples comparison to what its IT organization provides(New technologies): Deploying or developing for new technologies like mobile, big data and hybrid clouds can have huge impacts on the business of IT, from understanding the true total cost of applications for app rationalization, to business adoption of shared services and private clouds(New expectations): The business is now an active participant in the technology marketplace. They bring their own devices and expect IT to support them. And now that the business is getting price transparency for even infrastructure services in the cloud, they expect transparency from their own IT as well. What does all this mean for the business of IT? IT is on an fast path in transforming from technology provider to service provider. With a supply chain view we can more clearly see the decisions that affect the cost, utilization and quality of its services from end to end -- what we buy from whom at what price, how we build and run services, and how we manage business demand.Which of these trends are you seeing in your organization? What are the impacts you are seeing?
  • ATUM is based on management categories and best practice allocation methods distilled from the TBM Council and hundreds of Apptio customers across industries, sizes and geographies. Because ATUM is aligned with categories and costing methods used in Apptio Infrastructure Benchmarking, you can use Apptio to automate benchmarking with apples-to-apples comparisons to your peers.
  • A TBM Advisor is DEDICATED to helping customers understand and ADOPT Technology Business Management within their organization and identify new ways to gain VALUE from their Apptio subscription.We have broad knowledge and experience in IT Finance as well as IT Operations.... So by listening to our customers first, we are able to align our product to your process and assist you with building a TBM Adoption roadmap that is right for your business.Why am I talking about DQM? What experiences do I have?Data quality is a broad topic and means different things to different people… but I think everyone agrees that it can have quite a significant impact on an organizations ability to run an efficient businessAn example I can recall early on in my career when I was a mid-level manager for a large IT Outsourcing companyExample of Telecom Services DQ issues early onThe significance of data quality and data integrity is foundational to having a productive relationship in business. You can’t talk strategic until your house is in order…In todays presentation you will learn 3 main things:Data Quality Governance and how it relates to TBMYou will learn the 5 data quality dimensions that can be measured within the Apptio platformYou will learn the process and approach of handling Data Quality within Apptio
  • One of the biggest challenges I’ve heard from people wanting to start the journey of TBM say that they don’t want to start TBM because of poor data quality.Well, first, let me quote the famous Chinese philosopher, Lao Tsu – “A journey of a thousand miles begins with a single step”… That first step begins with data… and remember, data is foundational to driving better business decisions.To add, Apptio has taken the learnings based on over 140+ customers and developed IP around the concept of Master Data Sets… which is basically our definition of the most commonly used fields within each dataset that will help generate actions and decisions that generate measureable value… So we can tell you what data that you need so your scope around data quality is targeted only to the fields that we recommend based on our best practices.Another big challenge I hear is that people don’t have enough confidence in the level of DQ to defend the allocations within the Apptio model.And to that I say Embrace failure, take risk, and let me quote the Irish Author Samuel Beckett – “Ever tried?, Ever failed? No Matter, try again, fail again, Fail better”This quote reminds me of my friends at DIRECTV where thy have embraced a 12 point program that can be summed up as “Fast to Fail” where they just want people to recognize failure faster so they can learn from their mistakes and pivot to move forward again without blame or blowback from the organization.
  • Data quality can be measured in several different dimensions. When choosing these dimensions for Apptio, we had 3 basic requirements: 1) Does the dimension apply to TBM 2) Can we quantitatively measure it in Apptio? 3) Will our customers derive value in the output to help them make better decisions?So we start withMaintainability which is a measure of how easy it is to extract the data from the source system as well as the degree to how much the data is manipulated before it gets loaded into Apptio...Uniqueness is a measure of unique rows… the inverse of uniqueness is duplication… so we are checking for duplicate records in the dataCompleteness is a measure of the fields that have a value, so we are checking and reporting on blank valuesValidity is a measure of the values within the dataset compared to a set of allowed values. So this dimension requires a set of “Master” lookup values to compare againstFrequncy Distribution is the number of occurrences of unique values within a column. A low number of occurrences in the column will translate to “noise” in reports and is an important factor to consider when trying to discover value insights with the data
  • The ecosystem of Data Quality spans many facets. It starts by setting up the right governance with proper sponsorship and ownership. The data advisor helps accelerate what data you need so you can define what data sources you want to go afterData Governance, Ownership == Sponsorship and support systemData Advisor, Data Sources, and Data Stewards == Implementation (doing the work)Change Management, ADM, Monitoring == Continuous Improvement
  • The Ecosystem of TBM… Data Governance Vision and Strategy… as well as the Ownership (TBM Office).
  • Data Advisor defines what data that is required in order to build our out of the box templates.You have the ability to review all the required attributes by component and determine whether or not it is important for your organization. This greatly reduces the scope the Data Quality initiative will encompass and increase the chances of success.
  • Once you have defined the data sources and the associated attributes that map to the data advisor, the next step is to understand how each attribute is updated in terms of change management processes. For example, Dell found an error in their processes that the Owner of the application was never getting recorded… so it was impossible to tie applications to business owners in terms of costing. When they realized that the Service Desk wasn’t asking the right questions and not requiring that field in their service management system, they modified their process to ensure that the App Owner was a required field. Fixing the DQ issue at the source is always the best, long term option if it is as simple as adjusting a process like this one.
  • Automation / ADM
  • An example of Adaptive Data Management in Apptio is how we use “Data Mapper”. On the left hand side is a list of attributes coming from our Master Data Tables. On the right hand side are attributes coming from the customers data. This aliasing technique is just one of the many ways you can apply ADM to quickly translate your data into Apptio’s solution.
  • Data quality initiatives require building off of the correct foundation layers… starting with strategy and governance… understanding the data you need, choosing the right source system to use and the processes behind them. Next, applying the dq dimensions to that data so you can measure progress over time… as well as leverage Adaptive Data Management techniques for quick time to value so you don’t always have to wait and fix data in the source systems… The result, is that you can have a DQ number that you can apply a heat map towards based on cost * DQ %... To get an idea for how confident the numbers are that you are looking at.
  • Walk them thru this Workflow
  • Here is the top level dashboard that shows our matrix of data quality dimensions by data set. This matrix allows you to quantify the state of data quality within Apptio for a given month. You can then drill into any one of these KPI’s to analyze and understand the score and take action to improve it…. So, we want to go through these dimensions in chronological order (or left to right) so we’ll drill into the Server dataset under the Maintainability dimension.
  • So Remember, Maintainability is the degree to how complex it is to extract the data from the source system and how much manipulation takes place prior to loading it into ApptioFor Maintainability, the user is required to answer 3 simple questions that tie back to the definitionWhat is the source system? Database, Excel, OtherRate from 1 – 5 how long it takes to extract data out of the systemRate from 1 – 5 how much data manipulation takes place prior to loading it into ApptioThe answers can be versioned by month as data load processes improve and the trend charts light up to show historical performance… hopefully for the better
  • Uniqueness is a measure of the number of unique rows… The middle of the page describes how to apply some of Apptio’s Adaptive Data management tools to manage duplicate records without having to fix the source systems… The table below is an exception based report showing the rows that appear to be duplicate
  • Completeness is a measure of the fields that have a value, so the table at the top shows the number of blanks per column… you can see that the columns in the top table align to the columns in the bottom table…
  • … so if I wanted to slice into CPU Cores and find all the records that are associated with the number in the top table, click on the slicer and the report will refresh with those specific records… Also, you can export the filtered results out to an Excel and give it to the data steward for remediation
  • Measure whether the values in the data match to a set of “Approved” values… But in order to generate the approved values, it requires some initial configuration,lets click into the Settings button …
  • On the left hand side is a simple step by step guide that walks you through how to setup this dimension. The first table on the right is an exception based table that shows any value that hasn’t been assigned “Valid” or “Invalid” during the configuration process. This is important because it will catch any NEW values caught in the source data to be Approved for this dimension. The far table is a list of all values and their approval status… it’s a rollup of all the tabs that we will go to next.
  • Each tab has a “Validity” column that is required to be filled out as “Valid” or “Invalid”. Blank values are new values coming from the source that have not been assigned… (They default to Invalid for the purposes of the score). After assigning values, don’t forget to save the table before moving to the next tab.
  • Back to the Validity page, you’ll notice that it has a similar look and feel as completeness, where the invalid values are listed in the top table, and then use the bottom table for discovery and helping with the remediation process. Use the slicers to drill into the records that pertain to the appropriate column… then check those values against the “Expected” values on the right hand side…
  • Frequency Distribution is the number of occurrences of unique values within a column. So here, you can review the frequency of column values for each column… The right hand of the screen describes how the KPI is measured as well as goes through step by step instructions of how to use and act on frequency distribution issues… Remember, the idea here is to reduce the number of values in a given column to ensure the best reporting experience possible...
  • So the first thing to do with this dimension is to set the threshold value, which is basically your tolerance for “noise”. What I mean my that is setting the threshold will calculate the number of rows that the KPI will calculate against… So as shown here, if you have 6874 records and you set your threshold value to 2%, then 2% of 6874 = 137 rows…
  • Then you take the 137 and insert it into the slicer to filter down the dataset to review all the values for inspection… Use the slicers to navigate column by column for this dimension…
  • Presentation from State of Iowa's Cost Transparency Journey at ITFM Week 2014

    1. 1. May 1, 2014 Effective Cost Transparency from Imperfect Data Todd Tucker – TBM Council/Apptio Kevin Teets – Apptio Deb Krueger – State of Iowa
    2. 2. © 2014 Apptio, All rights reserved.1
    3. 3. © 2014 Apptio, All rights reserved.2 The Importance of Why
    4. 4. © 2014 Apptio, All rights reserved.3 “Why” Questions in IT? Why do we need so much tier 1 storage?
    5. 5. © 2014 Apptio, All rights reserved.4 Business Capabilities Business Services Technology Services Application Services Platform Services Infrastructure Services Projects Resources FinanceViewITViewBusinessView Cost Pools General Ledger (Chart of Accounts) Cost Model Business Capabilities Business Services Technology Services Resources Value Chain Model Why? How? What? Our Value Chain…
    6. 6. © 2014 Apptio, All rights reserved.5 IT Cost Transparency is not about What does IT cost? It’s about… WHY does IT cost what it does? – and – HOW can we use our money and other resources to create MORE VALUE?
    7. 7. Transparency Every Business Needs For Fact-Based Decisions © 2014 Apptio, All rights reserved6 “We knew more visibility would enable a change in culture and facilitate more accountability. Every CIO should have the level of transparency that enables action.” HAROLD BOUTIN, Senior Vice President of IT Strategy and Effectiveness, Equifax A P P L I C A T I O N S What does it cost to provide each product and service? S E R V I C E S B U S I N E S S U N I T S L A B O RV E N D O R S S P E N D D A T A Q U A L I T Y 110010 011001 010110 P R O J E C T S I T T O W E R S What are the costs and KPIs of our key business disciplines? Who is consuming how much of what?
    8. 8. What Questions Can You Answer with Transparency? A P P L I C A T I O N S A N D S E R V I C E S B U S I N E S S U N I T S  What is driving the costs of our top 10 apps?  What are project vs. run costs for these apps?  What are cost levers for reducing cost of this app? APPLICATIONS  Which cloud services are we spending most on?  What is our cost per vendor for this service?  How do our IaaS costs compare to Amazon’s? SERVICES  What is our investment level per BU?  What does it cost to deliver these apps to this BU?  Where do we spend the most per employee? BUSINESS UNITS  How much are we investing for innovation?  How are we performing against project KPIs?  Which projects are exceeding planned resources? PROJECTS  What is driving our run costs?  What is our cost per GB of tier 1 storage vs. peers?  Are we trending toward greater cost-efficiency? IT TOWER  What types of vendors are we spending most on?  Are we leveraging preferred providers?  How are we doing against spend targets? VENDORS  Which costs are within our control?  Where are largest sources of plan variance?  What is driving plan variance? SPEND  What is driving labor costs by role, location?  How are we doing against our staffing plan?  Where are we using our staff? LABOR  Where are our cost blind spots?  Which data from what systems don’t line up?  Which data is getting stale? DATA QUALITY F O U N D AT I O N 110010 011001 010110 © 2014 Apptio, All rights reserved7 FINANCEIT EXECS TOWER, APP & SERVICE OWNERS BUSINESS
    9. 9. Where and When Would Better Cost Transparency Have An Impact For You? © 2014 Apptio, All rights reserved8  Questions from the business  Initiative (M&A, ERP migration…)  Business Case  Infra choices by app teams  Requests for capacity  Quarterly Business Reviews  Annual IT and Business Planning  Project Portfolio Prioritization  Exec / Leadership Meetings  Capital Review Board  Demand Planning ANNUAL AND QUARTER  Plan variance analysis  Management reporting on progress against targets MONTHLY AD HOC
    10. 10. © 2014 Apptio, All rights reserved.9 The Business Value of Transparency Clorox Co. has promoted CIO Ralph Loura to senior vice president and added him to the company’s executive committee. “We’re a 100-year-old company and for the first time IT is represented on the executive committee directly,” he said. One way Mr. Loura has been able to help shift the thinking about IT at Clorox is by using a model of financial transparency and fiscal discipline known as technology business management. – Rachel King, Wall Street Journal http://bit.ly/WSJClorox20140426 Ralph Loura SVP and CIO The Clorox Company
    11. 11. © 2014 Apptio, All rights reserved.10 What Does This Have to Do with Data?
    12. 12. Plan CapEx/OpEx Run/Grow/Transform Fixed/Variable Location/Regions Month/Quarter/Year Cost Centers Accounts General Ledger Line Item Detail B R E A K O U T S Standard IT Cost Categories Application 1 Application 2 Application 3 Application 4 Application & Integration Delivery Services Hosting Services Professional Services Client Computing Communication & Collaboration Connectivity End-user Support Records Management Business-Driven Initiatives Infrastructure Initiatives Process Initiatives Compliance Initiatives Your Applications Technology Services End User Services Project Services COST TRANSPARENCY: APPLICATIONS AND SERVICES Design & Develop Buy, Build & Deliver Market & Sell Service Customer Shared Services BUSINESS CAPABILITIES Business Unit 1 Business Unit 2 Business Unit 3 Business Unit 4 COST TRANSPARENCY: BUSINESS UNITS = Peer Benchmarks Available Hardware Software Internal Labor External Labor Facilities/Overhead Outside Service FOUNDATIONApptio TBM Unified Model™(ATUM™) IT TOWERS & SUB-TOWERS COST POOLS Data Center Compute IT Operations Voice Network Delivery Services Security & Compliance User Services Data Network Storage Application IT Management COST TRANSPARENCY: FOUNDATION Wintel Servers Linux Servers Unix Servers Locations Mainframe Tier 1 Tier 2 Tier 3 Tier 4 Office LAN DC LAN WAN Internet MAN Voice premise Wide Area Voice Call Center Project Mgnt Client Mgmt PCs Mobile Device Service Desk Field Service App Dev App Support QA (Testing) Middleware Software Lic. IT Mgmt & Admin IT Finance IT Vendor Mgmt Ops Center Service Mgmt Security Compliance Disaster Recov. Architecture
    13. 13. Data and Allocation Methods (Example) © 2014 Apptio, All rights reserved12 Hardware Software Internal Labor External Labor Facilities/Overhead Outside Service FOUNDATIONApptio TBM Unified Model™(ATUM™) IT TOWERS & SUB-TOWERS COST POOLS Data Center Compute IT Operations Voice Network Delivery Services Security & Compliance User Services Data Network Storage Application IT Management FOUNDATION = Peer Benchmarks Available Wintel Linux Unix Locations Mainframe Tier 1 Tier 2 Tier 3 Tier 4 Office LAN DC LAN WAN Internet MAN Voice premise Voice WAN Call Center Project Mgnt Client Mgmt Workstation Mobile Device Service Desk Field Service Development Support QA (Testing) Middleware Software Lic. IT Mgmt & Admin IT Finance IT Vendor Arch. Ops Center Service Mgnt Security Compliance Disaster Recov. Sub-Tower Composition by Cost Pool Used to configure mappings & allocations from your unique GL  Linux Hardware: Dev, Test & Prod Servers, Internal Storage…  Linux Software: Operating System, Virtualization…  Linux Labor: Engineering, Tech Support Unit Metrics  Per physical server, per logical server, per CPU, per CPU Core Sub-Tower to Application Allocation Allocation Data  Good: App & server team estimates (top 20 apps)  Better: Server list with supported apps (e.g. top 20 apps)  Best: Server performance by app ID Allocation Methods  Assumptive: Appx % of all LINUX used by each app; or  Data: 1:1 relationship of server to app; or  Data: 1-many relationship, weight by avg. CPU usage Linux
    14. 14. Challenges of Creating Cost Transparency TRIGGERS  Month end close  Forecasts  Project financial  QBRs  Ad hoc questions MANIPULATE DATA  Clean and manipulate  Create joins and mapping  Find data problems 110010 011001 010110 3 BUILD REPORTS  Create pivots  Build graphs  Find data problems 5 MAINTAIN COST MODEL  Build vLookups  Debug Formulas  Find data problems 4 VERSION CONTROL! ORG CHANGE! Update Own Cost Spreadsheets DATA SOURCE CHANGE! VALIDATE/CLARIFY6  Timing and categorizations  What cost went where?  Why is that in MY costs? FINANCE High: $3.8m Low: $180k DATA OWNERS High: $225k Low: $18k DEPARTMENT OWNERS High: $108k Low: $11k IT EXECUTIVES High: $130k Low: $11k PROVIDE DATA  Extract  Validate 2 110010 011001  Explain  Fill gaps PUBLISH REPORTS  Trick Excel into making waterfall charts  Annotate and distribute 7 REQUEST DATA 1  Prompt IT and corporate for data extracts ANSWER QUESTIONS9  Answer requires more granularity or different slices  Answer requires more dats (may become a “study”) ASK QUESTIONS8  Why did costs. KPIs change?  What does this include?  I need to see this slices by…  What it…? ? The cost of staff time spent on manual IT cost analysis shows wide range of breadth, scope across Global 2000 IT orgs
    15. 15. © 2014 Apptio, All rights reserved.14 Which Comes First: Transparency or Good Data? “There's no better way to focus and prioritize your cleaning up data like assigning costs to it. If you know that your ‘unknown’ is costing you a lot of money each month, you‘ll choose do something about it.” – Lance Warner TBM Architect First American Financial Award for Business Transformation: First American Financial TBM Conference 2013
    16. 16. May 1, 2014 Cost Transparency at State of Iowa
    17. 17. © 2014 Apptio, All rights reserved.16 Mission: Provide Iowans unified, comprehensive, value-driven administrative services  Responsible for infrastructure IT services to Executive branch agencies  Goal of reducing the cost of government by 15%  Consolidation of executive branch IT infrastructure functions is in focus  Federal law requires all services sold to agencies be at a net zero recovery  State agencies could approve/disapprove of certain rates charged by DAS-ITE  Department of Management oversees rate setting, determines if rate changes are allowable  IT has proven more difficult for users of financial information to understand Why Cost Transparency at State of Iowa
    18. 18. May 1, 2014 Working with Imperfect Data
    19. 19. © 2014 Apptio, All rights reserved.18 Introduction 1. TBM ADVISORS – MISSION STATEMENT 2. WHY AM I TALKING ABOUT DATA QUALITY? 3. WHAT YOU WILL GET OUT OF TODAY’S PRESENTATION?
    20. 20. © 2014 Apptio, All rights reserved.19 Challenges Don’t want to start TBM because of poor data quality Do not have confidence in the level of data quality to defend the allocations within the Apptio model START NOW! “A journey of a thousand miles begins with a single step.” – Lao-tsu, The Way of Lao-tsu – Chinese philosopher (604 BC – 531 BC) EMBRACE FAILURE! “Ever tried? Ever failed? No matter, try again, fail again, fail better.” – Samuel Beckett – Irish author, dramatist, novelist in France (1906 – 1989)
    21. 21. © 2014 Apptio, All rights reserved.20 Apptio Data Quality Dimensions – Defined MAINTAINABILITY A measure of the degree to which data can be accessed and used, and the degree to which data can be updated, maintained, and managed. UNIQUENESS A measure of the number of distinct or unique values within a field. COMPLETENESS A measure of the count and percentage of the fields that contain a value. Example: A server Operating System has a value in 90 out of 100 records, Data Quality Completeness = 90%. VALIDITY A measure of the values within the data set compared to a set of allowed valid values. Example: Test all values in OS to a master set of valid values to ensure there are no outliers. FREQUENCY DISTRIBUTION The distribution of unique values within a field by count and percentage. For those values with a low frequency, consider dropping them and changing to another comparable value. APPTIO ON DEMAND
    22. 22. © 2014 Apptio, All rights reserved.21 Data Quality Ecosystem Data Governance Ownership (TBMO) Data Advisor Data Sources Data Stewards Change Management Automation & ADM Monitoring / Measurement Data Quality
    23. 23. © 2014 Apptio, All rights reserved.22 Data Governance Organizational Model OFFICE OF THE CIO Executive Sponsorship Business Strategy Ownership Strategic LeadsData StrategyPolicies &Standards Tactical Technical& Business Process OwnershipData &System Architecture Data Management Stewardship controlanddata management Data Governance Program TBM Steering Committee TBM Office CROSS FUNCTIONAL WORKGROUP DATA STEWARDS OwnershipPolicy
    24. 24. © 2014 Apptio, All rights reserved.23 Data Advisor Data Advisor defines the data that you need to build out each component within Apptio, effectively acting as the Master Data set for each source.
    25. 25. © 2014 Apptio, All rights reserved.24 Data Quality Integration into Change Management Change Management • Maintainability • Uniqueness • Completeness • Validity • Frequency Distribution
    26. 26. © 2014 Apptio, All rights reserved.25 Apptio Adaptive Data Management DISPARATE RAW DATA • Data checks • Parse, filter • De-dupe • Create • Change • Join • Auto-discover source data relationships • Map source to model objects • Visualize relationships VALIDATE AND CLEANSE RELATEENRICH RULES-BASED TRANSFORMATION DATA INFERENCE MODELS & ANALYSES EXTRACT Connectors (Cloud or On-Prem) CORRELATED MAPPED DATA • Continuously adapts to changing data and analytics needs • Data chain of custody preserved and documented • Less time on data prep, more time on analysis and decisions DATA QUALITY DIMENSIONS
    27. 27. © 2014 Apptio, All rights reserved.26 Data Mapper Data Advisor Master Data fields that support our Out of the Box content Customer data that is mapped to Master Data which enables the fastest configuration possible
    28. 28. © 2014 Apptio, All rights reserved.27 Data Foundations Data Strategy Data Governance Source Systems Data Quality Dimensions Adaptive Data Management Data Quality Index Transparency Owner ship Apps GL Completeness Servers Maintainabilty Labor Validity Frequency Distribution = DQ Ave % * Impact $$
    29. 29. © 2014 Apptio, All rights reserved.28 Data Quality Workflow
    30. 30. © 2014 Apptio, All rights reserved.29 Data Quality Dimensions – Dashboard Drill into any KPI for additional detail
    31. 31. © 2014 Apptio, All rights reserved.30 Data Quality Dimensions – Maintainability Answer 3 questions to evaluate score
    32. 32. © 2014 Apptio, All rights reserved.31 Data Quality Dimensions – Uniqueness Total number of duplicate records
    33. 33. © 2014 Apptio, All rights reserved.32 Data Quality Dimensions – Completeness # blanks per column
    34. 34. © 2014 Apptio, All rights reserved.33 Data Quality Dimensions – Completeness Slice into each column to discover the rows causing the errors Export out for remediation Row count is the same as # blanks above
    35. 35. © 2014 Apptio, All rights reserved.34 Data Quality Dimensions – Validity First – configure Settings Invalid cells are based on values set in Settings
    36. 36. © 2014 Apptio, All rights reserved.35 Data Quality Dimensions – Validity Settings Instructions Values that are new and have not been assigned
    37. 37. © 2014 Apptio, All rights reserved.36 Data Quality Dimensions – Validity Settings Assign “Valid” or “Invalid” as appropriate. These values serve as the “Master” lookup values Change values and click Save before moving on
    38. 38. © 2014 Apptio, All rights reserved.37 Data Quality Dimensions – Validity # Invalid values per column Compare against expected values
    39. 39. © 2014 Apptio, All rights reserved.38 Data Quality Dimensions – Frequency Distribution Instructions and overview of calculation
    40. 40. © 2014 Apptio, All rights reserved.39 Data Quality Dimensions – Frequency Distribution Review Threshold Row number Set Threshold Value
    41. 41. © 2014 Apptio, All rights reserved.40 Data Quality Dimensions – Frequency Distribution Adjust slicer settings and insert Threshold Rows KPI to review items for inspection
    42. 42. © 2014 Apptio, All rights reserved.41 Data Quality Maturity
    43. 43. May 1, 2014 Data Quality Journey at The State of Iowa
    44. 44. © 2014 Apptio, All rights reserved.43  Data comes from many different and varied systems  HRIS, general ledger system, MS Project, eDAS, etc.  Buy in is important!  Culture change comes from executive decision that transparency is important  Transparency cuts both ways:  view into financial data, which can be powerful and useful for asking for rate increases  shines a flashlight onto data quality (or lack thereof…)  Many stakeholders can have strong opinions about the data  Don’t wait to begin transparency efforts due to data quality Data Quality Is a Sensitive Subject
    45. 45. © 2014 Apptio, All rights reserved.44  Explained that financial data isn't 'perfect' and gets better with everyone's help  Managers have responsibility to review financial information  Managers ask for help where numbers disagree with their 'gut' feelings  Sometimes the financial data shows:  something that might have been forgotten or…  the financial data and/or allocations need to be adjusted  Iterative process – no financial report is considered above question Roadmap to Improve of Data Quality
    46. 46. © 2014 Apptio, All rights reserved.45  Semi-annual inventory of servers, ports, racks  Ease the burden of reporting in ledger to having the costing tool (Apptio) provide the costing analysis  Allow billing to have additional 5 days each month to perform  trend analysis  review additions/deletions to prior month's file  Build good relationships with technicians, so coding changes can be made  Restrict access to 'master' data files  Bring in software to build a CMDB (implementing ServiceNow)  Monthly reconciliations to billing files and ledger to assure pass-through costs are recovered Outcomes to Date
    47. 47. May 1, 2014 Building Trust in Our Data
    48. 48. © 2014 Apptio, All rights reserved.47 Steps to Improve Trust in the Data  Beta test new models or major changes  Be transparent about data quality  Account for every dollar  Ensure report consumers understand:  how the costs were allocated  how to interpret the reports  what changes they can make  Provide drill downs in your reporting
    49. 49. May 1, 2014 Where To Learn More
    50. 50. © 2014 Apptio, All rights reserved.49 Apptio Resource Center Top 5 Reasons for Avoiding IT Cost Transparency (May 6 Webcast) http://bit.ly/apptiomaywebinar Key Considerations in Data Model Whitepaper http://bit.ly/apptiokcdmwp Case Studies: AutoTrader Group (http://bit.ly/apptioatg2014) CME Group (http://bit.ly/apptiocmeg2014) Freddie Mac (http://bit.ly/apptiofreddie2014) Product Info: Cost Transparency Foundation (http://bit.ly/apptioctfds) Source Data Guide (http://bit.ly/apptiosdrg201404)
    51. 51. © 2014 Apptio, All rights reserved.50 TBM Council  TBM Conference in Miami  Workgroups  CXO peer groups for vertical industries: FSI, Insurance, Health, CME, Energy, High- Tech  CFO of IT, Planning & Strategy, and Enterprise Architecture  TBM Book  TBM Index  LinkedIn Forum (http://bit.ly/TBMGenMembers)www.TBMCouncil.org
    52. 52. TBM Conf 2014 Miami – fountain blue 2014 Miami TBMconference.org October 28-30
    53. 53. 52 Thank You! Todd Tucker TTucker@TBMcouncil.org Kevin Teets KTeets@Apptio.com Info@Apptio.com Apptio.com

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