79 Accelerate your Journey: How to create an Analytics Center of Excellence. Chris Mundy, Alex Lee Corporation Katie McCray, IBM

Transcription

1 79 Accelerate your Journey: How to create an Analytics Center of Excellence Chris Mundy, Alex Lee Corporation Katie McCray, IBM

2 What is an Analytics Center of Excellence Centralized Support Centralized Activities

3 Agenda Self Evaluation Understanding Your Options Charting the Course The Alex Lee Corporation Story IBM Analytics University 2018

4 Step 1: Self Evaluation 1) What are my strategic priorities? Do any of these sound familiar: We want to enable our business users with self service All of our decisions will be data and fact-based everywhere We will infuse cognitive analytics into everything we do We have a new Cloud First strategy 2) Where are we in our analytics journey? Where do we plan to be next? Ultimately? Traditional BI Self Service Analytics Self Service Data Prep Citizen Data Science Cognitive Analytics 3) What are our strengths and weaknesses? Be brutally honest: What shape is our Data in? Do we have skilled People throughout our company? Is Technology aiding or leading our outcomes? Do we have and obey clearly understood Processes?

5 Step 2: Understanding Options Communities of Practice Group of like minded people informally getting together to discuss topics and set standards May or may not have a specific problem to solve May or may not have executive support Competency Center Strategic and defined entity with a mission and executive support Few full time staff, staffed mainly with part-time members who are borrowed from other teams Center of Excellence / Transformation Center Strategic and defined entity with a mission and executive support Fully staffed internal consultancy team Typically formed to solve a business alignment or transformation gap Often has a temporary mission that dissolves once the business transformation is complete, and the team takes on a new mission or is dismantled Squads, Tribes & Guilds Typically associated with the Agile approach Some companies are also creating these teams outside of Agile, eg. Analytics Enablement Squad

6 Step 3: Research, Define, and Get Approval Topics to address: What is our mandate, our mission? Who are our champions, our stakeholders? What is our roadmap, key dates? How will we be funded? How will we be measured? How much authority and influence will we have? What services and activities do we own? What do we not do? Which services are free to the business units, which have a fee? What roles and skills do we need? How will we staff them - Full time, borrowed, consultants? Who do we support, entire company or certain groups? How do we engage with other teams? How do others know we exist? *Detailed slides on these topics are in the appendix, if you wish for more guidance and examples

7 What are our strengths and weaknesses? Identify Strengths and Weaknesses regarding analytics Interview people across the organization Tease out the common threads and statements Examples might be: Strengths Culture Highly skilled is open professionals to change Motivated employees Supportive Leadership Company is open to new ideas Great company culture Weaknesses Fragmented, IT is over burdened, Silos slow turnaround IT is over burdened, slow turnaround Too much time cleansing data sets Not enough self service Little knowledge sharing Outdated reports and dashboards Niche, rogue tools spread across the enterprise

8 What is our mandate? Mission statement Executive approval Alignment to strategy What do we do What don t we do Have an elevator pitch How long will it exist? Temporary or long term? Is it design to transform? Broad example: Our mission is to enable and empower our business users across the enterprise using analytics to improve business outcomes. Targeted example: Our mission is help our sales and marketing teams better understand the new market landscape using data science techniques. We will help them grow their skills, learn new analytics tools, and adopt a new way of working.

9 Who are our champions? Who is our chief sponsor? Chief Financial Officer Chief Operations Officer Chief Data Officer Chief Analytics Officer Stakeholders / Steering Committee? Business leadership representatives Technology leadership representatives Project office leadership representatives Senior business experts Senior technical experts

10 How will we be funded? Examples: Direct executive funding Charge backs Business units pay per: Project where your team is engaged User using your tools and data Size of their team relative to others Service requested of your team Every business unit contributes a nominal amount for standard services, then pays more when using your custom services In what currencies, if serving global community A little of everything above

11 What activities do we perform? Standard Activities: Enablement Governance Master data management Solution design and reviews Best practices Consulting First of a Kind pilots Gap analysis Readiness assessments Data and report certifications Additional Activities: Will we operate and manage a data environment? Will we own the entitlements to the analytics tools and reports? Will we own the upkeep of the analytics tools (installs, patching, etc...)?

12 What services do we package? Position your services like a small consultant firm Define your services relating to your mission Package them Market them Sell them Example of services opportunities to sell: Analytics Quality Review A service where your experts review a user s reports, dashboards, analyses to make suggestions on design, action-ability, accuracy, or performance. Analytics Guardian Services An ongoing service where your experts provide advice and mentorship to business users on a regular, recurring basis. Solution Design A service where your experts help design and validate a new analytics solution for a requesting business unit Data Preparation A service where your data engineers help business users prepare their data, especially with complex situations

13 What roles and skills do we need? Consider roles: Leader Solution leads Technical architects Data stewards Training and Enablement staff Project coordinators Consider skills: Entrepreneurial spirit Best of the best skilled experts Diverse skills across team Strong network across organization Willing to challenge and be challenged Soft skills, communication skills Can work independently with little guidance Where will we get our people: Hire new? Pull from other teams? Borrow others temporarily or full time?

14 How do we engage with other teams? How do teams reach you? Chat and messaging tools Formal ticket process Project request Internal contract from one department to another Pick up the phone and call How do you borrow staff from other teams when needed? Staffing coordinator Internal contracts and agreements Keep it simple, and make sure everyone is aware of your value and existence.

15 How do others know we exist? Marketing your team is important Make sure others know: What you do What you ve done The value you bring Ask for feedback Showcase your success stories Newsletter Executive reviews All hands calls Events Promote feedback such as: The Analytics Center of Excellence was indispensable to our project. We could not have overcome the hurdles we did without their expertise, mentorship, and extended relationships.

16 How will we be measured? Your measurements should match your mission and goals. Measuring your success not only tells you how you re doing, but it: Builds trust and confidence in your stakeholders and customers Helps you know when to change your mandate Some examples: Number of capital projects supported Time spent on approved projects Retention rates of allocated staff and extended named staff Customer feedback Number of business decisions impacted Be careful of measurements that: Don t align w/ the corporate strategy Aren t influenced by your activities Aren t valued by the stakeholders and leadership

17 Step 4: Implementing Clearly define & communicate the new organization, leave no confusion Don t be afraid to get help (internal business partners, external industry experts, etc ) Be realistic How likely will you receive the funding you requested? How quickly can you transition existing employees and hire new employees? Realize ramp-up for new teams and duties takes time Don t overcommit or overpromise Pilot with 1 or 2 trusted business units before rolling out It always takes time to work out the kinks Market & socialize your new team when you re ready to rollout Learn and Evolve as you go Ask for feedback often Criticism is often a good thing it means people are leveraging you & care enough to see it improve Keep up w/the changing business and industry landscape Be prepared for push-back if you re applying new governance and rules to what was previously the wild west Ultimately, do what you say - Trust is key!

18 Understanding Options ACE 9/18/18 18

19 Case Study: The Alex Lee Corporation Our evolving journey to an Analytics Center of Excellence IBM Analytics University 2018

20 About The Alex Lee Corporation We Feed People Retail Division and a Wholesale Division Retail Grocery Stores operating across 2 banners Wholesale 1 Million Square Foot Distribution Center serving over 1000 grocery stores across 12 states Our Retail data warehouse is an extension of an Oracle Loss Prevention application purchased 20 years ago Which is no longer in business Our Wholesale data warehouse is an extension of our retail data warehouse Probably not the best strategy We re now beginning to realize the value and power of our data and are taking steps to build an Analytic Center Of Excellence 9/18/18 20

21 Our old approach to COE (Center of Exasperation) - No analytic strategy - No concept of an analytic job family - Limited communication - Little visibility to prioritization - Only a few dedicated resources IT (corp) Retail Wholesale Open Open Oracle DBA Open Borrowed Sr. Analyst Sr. Analyst Category Analyst Category Analyst Manager Sr. Analyst Marketing Analyst Add data to DW Build packages Maintain Cognos Supporting Category Management Out of control data wrangling Juggling multiple reporting tools Fixing IT issues Supporting Sales & Marketing Out of control data wrangling Juggling multiple reporting tools

22 Self Evaluation (2017) DAT A Data Warehouse is unorganized & poorly structured Missing necessary data items Not capturing data (Accounting Adjustments) No accepted view of common metrics & hierarchies Poor quality of data No business glossary or definitions PEOPLE Understaffed Existing resources are exhausted Not everything gets done that should Difficulty growing business partnerships Hard to provide proper decision support Business partners don t know what s available Missing SME skills - advanced analytical & statistical Little Knowledge sharing across teams TECHNOLOGY/ APPLICATIONS 7 versions behind in Cognos Analytics Too many 3 rd party tools no holistic governance Too many requests for data dumps Minimal exception reporting, No dashboards Difficulty providing a reasonable self service platforms Unable to leverage advanced predictive sciences Lacking automation PROCESS No active Executive sponsorship No formal prioritization of requests Data warehouse & analytics is an afterthought Not included in project planning, causing delays No governance of data quality, 3 rd party tools, security, standards, definitions, or operations Lacking formal Path-to-Production lifecycle process 9/18/18 22

23 What did we do? After self-evaluating, we knew we needed to change. We: Investigated the needs of the company, divisions, and functional areas Learned everything we could about what options are out there, what other companies are doing, and what the industry analysts are recommending Leveraged partners, LPA & IBM, to help us: Understand our options Put together a realistic plan that allowed for evolution & growth Implement our new team, technology, data & analytics activities and processes 9/18/18 23

24 Our new, evolving COE (Center of Excellence) - Built an analytic strategy - Joint IT prioritization - Improved ongoing communication - Created an analytic job family - Added headcount IT (corp) Retail Wholesale Director Information Architect Director, FP&A Lead Financial Analyst Director, FP&A Information Analyst Information Analyst New Team - IT BI & Analytics Redefined job family, roles Moved Cognos to the Cloud Partnership w/it & Analysts Supplement with consultants Sr Financial Analyst Sr Financial Analyst Data Analyst Sr Financial Analyst Added Director to develop team Added resources with expanded skills Transitioning to business insights instead of just reporting Manager, FP&A Financial Analyst Manager, FP&A Manager, FP&A Sr. Financial Analyst Sr. BI Analyst Expanded team Expanded Partnership across business Growing analytics capabilities Using new Cognos capabilities for more efficient reports and self service analytics

25 Where we are today DAT A Collaborated with the Data Analysts and LPA to design a new warehouse that is optimally structured and organized for ease of reporting and analytics Collaborated with the Data Analytics Team to identify operational data gaps and included these fields in the new data warehouse Collaborated with the Data Analysts and identified 13 metrics, with 32 unique groupings which will ultimately eliminate the need for multiple sources and tables which lead to confusion Slowly establishing the data warehouse as the source of the truth for data Started to engage with the Data Analysts to create a business data dictionary to effectively create the framework data model PEOPLE Added additional capacity (skills and resources) Reorganized to create an Analytic Community across the organization (chart follows) Added advanced analytic/ statistics and data SME skills Began communication and best practice sharing amongst the IT and analytics teams (user groups, steering committee) Attached an IT Analytic resource with each of the business partners to assist with knowledge transfer and assisting with advanced reporting services to create an Analytic Community amongst the technical and business environments TECHNOLOGY/ APPLICATIONS Partnered with IBM using their Bridge to Cloud offering to eliminate the need for ongoing Cognos upgrades and sunset the on-premises Cognos environment Partnered with LPA to develop efficient cubes and packages Setting the stage for dashboard development Providing the foundation to remove the need for 3 rd Party tools and putting the power of the data in the hands of the users to eliminate the requests for data exports Taken a more proactive approach with data modeling Partnered with LPA (short term) to develop reporting that leverages multi-dimensional data sources Partnering (long-term) to train our Analysts using our data PROCESS Governance processes are beginning to take shape (data quality, 3 rd party tool selection, data definitions, etc.) Data warehouse, reporting & analytics is gaining support from the users for projects/ project plans; appropriate stakeholders are now participating in upfront planning Creating a Path to production for standardized, recurring reporting & dashboards is underway shifting these tasks from business users and analysts to automated IT processes Implemented a 6-week Analytic Steering Committee prioritization processes for Analytic IT requests/ data needs as well as for new analytic projects We now have Executive Sponsorship!!!! 9/18/18 25

26 Summary Self Evaluate Understand your options Research, Define, & gain approvals Implement Evolve

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28 Appendix IBM Analytics University 2018

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