Making a Modern Data Centric Organization — Part 3
How to make a Data Centric Organization? — Technology
Technology
The Third element on how to make a Modern Data Centric organization is Technology.
There are 2 focal points
(1) to have a clear roadmap for modern data centric organization
(2) to choose the right data infrastructure for your modern data centric organization.
For having a clear Roadmap to create modern data centric organization,
i think it has 5 phases
First, is the IDENTIFICATION — Find the growth or data value gap and Identify success criteria
Second is to Optimize — Free up your Money and Resources & Optimize Data Ecosystem
Third is to Innovate — Use Money to build capabilities
Forth is to Transform — Use Capabilities to Modernize
Fifth is Continuum — Continuous improvement
Identify:
1. The first phase of the roadmap to making a modern Data organization is “Identification”.
The first essential step is to understand the status quo and shake it up.
The Identify phase to find your Data Value Gap from Business, technology, Process and People..
Setting up KPI and identifying “Critical Success Criteria” for building a Data-Centric organization. How the Data is adding value today and how you intend to add value to the organization using data in the future determines the path and dollar needs to be spent for the Modern Data Organization.
Data belongs to everyone in the organization and is the start, center and end of everything an organization does. The use of the data from root node to leaf node, from Board room to engine room to shop room influences their day-to-day work and decision making that determines the Data mindset in the organization.
- Is Data Strategy in sync and aligned with your organization and Business strategy?
Why do you want to make a Data organization and what is the target growth in business or cost savings or maintenance optimization you expect out of it? The first step to making a data organization is not to identify and get a laundry list of all the latest Data technology trends in place but to first “identify your Data value gap” that will automatically take you to the “Data innovation gap” and how to fill it.
Is Data considered s an Asset for your business?
Ultimately what you should understand is, by leaving your Data platform as it is, will it hamper the business performance? Will this be any reason for the likely decline of your business performance over time and which areas are they?
How can you deduce this? Say if you are going to release a Data IPO as it is for your firm today, how much do you think you can provide a numeric value to your organizations Data at this point in time? Data is in the center and using the modern Data platforms is your ecosystem how you want to treat your data and what outcomes you expect out of the data.
Define your core parameters:
Defining the core parameters for your Data Centric Organization:
People
What are your Data Team personas? Define them from CIO/CTO, CDO, Data visionaries, EA, Data Security expert, Legal, Data Analyst, Data Scientist, Data Warehouse users, Admin etc.,
Have the Job description ready for all these roles.
Ensure that the critical roles are hired.
Buy-in and Initial Funding
Know your sponsors
Prep them on the guestimates funding and pre-wire all your team who could support the buy-in.
Functional
Security, User experience, Data, Interoperability, Infrastructure, Interfaces, network, Middleware, Connectivity, Configuration.
Non-Functional
Performance, Scalability, Throughput, Reliability, Extendibility, Manageability, Serviceability.
Operational
SLA, Schedule, support, volume, time to market, storage growth, latency, DevOps, Code & Security coverage etc.,
Implementation
Architecture patterns, isolate — loosely coupled, service / servers, which of the 7R’s approach, Security by design.
Cost / Funding
Operational efficiency — Reduce maintenance with automation and move budget into innovation and slowly ensure funding for Innovation.
Once the core parameters are defined, you must
1. Define the Block level architecture
2. Put up a SWOT analysis for your current data platform
Top 10 key functionalities offered by your current platform for your business.
Top 10 dependencies / challenges to move away from your current Data platform.
Top 10 problems if you have to continue with your current Data platform
3. Top 10 strengths and weaknesses that your current architecture offers
4. Top 10 strengths and weaknesses your new architecture option offers.
5. What are the future strength / top 10 features you want to have in the new architecture / Data platform? Prepare a list for both short-term and long-term.
6. measure your trade-offs Cost Vs. Maintenance
Optimize:
Next comes optimize , first step is for yu to understand the past 3 year’s budget and how much you are spending for Maintenance or manual operations and how you can chanalize those funds for data innovation. Your core of optimization should be two parts
Part A: Free up your Money and Resources.
Free up your money from the maintenance / manual process or where technology is handled by business into automating solutions. Embrace or leverage automation so that your maintenance budget can be channelized or tuned towards your innovation budget.
Free up your resources from your day-to-day maintenance tasks and channelize their energy towards Innovation. Start with Data Literacy and train all your resources to be Analyst, who understand data — that should be the bare minimum criteria.
Part B: Establishing optimal environment for Data organization.
Understand your workloads. Is your complexity of data increasing? Is the volume, variety, velocity, and value of your data increasing? If yes, by how much. Will it work fine in the existing setup, or either the Tools or the workloads or the processing or the environment should be optimized?
From both Business and Technical side, do you want to improve the user experience? Are they happy with the current access of Data? If changes are needed, where? Who are the user personas, who have issues with accessing your data?
To Optimize, we must focus on 3 key aspects
What it takes to make a modern data organization
Your firm’s business & data strategy marrying the modern data platform
Best practices specifically for your organization to optimize Data-Centricity.
Innovate:
Now, let us assume you have asutomated and freed up money and resources.. as part of innovate, use the money to build capabilities.
Building islands of capabilities then you expand from there. You may have inhouse expertise on blockchain, champions in Data Platform on Azure — now you fund those projects to build these projects so they will champion.
To Innovate effectively,
1. the primary factor you should have is “Funding” — Money. Either you can release this money from the maintenance and manual operations by leveraging automation and channelize the sources towards Innovation.
2. The second factor you should focus on is the Resources / Team. Having a ideal team size — there are several theories to it, two-pizza team, small teams — scrum team or squad teams of 8 members etc., and these resources / small teams should be well aligned to the Domains so that there are very clear and defined responsibilities with clarity of vision and single focus. Continuously Modernize the resources and provide a bare minimum framework and a roadmap for the resources to adopt.
3. The third factor you should focus on to build Innovation is the “Processes”. Enabling DevSecOps, Test Driven Development, Continuous Delivery, Data Governance, Cloud Native for Modern Data Platforms and process to adopt Open source where applicable will go a long way. This will enable us to think long-term rather than short-term.
4. Bring up your Data Platform strategy
You must have defined the core parameters for your Data Platform (1) Functional (2) Non-Functional by now.
Build a comprehensive Data Strategy. Your strategy should provide clarity on…
1. The How: How to build Data of value to meet the Organization goals and business strategy
The How: How the organization will have to complete the desired data activities to achieve its objectives
2. The What: What all needs to be changed in order to maximize the value of the Data and activities and outline plans as to how the organization should make these changes in terms of People, Process, Technology, Funding, strategy etc.,
3. The What: Provide clarity on how the specific Data activities can enable the firm to realize its Business goals, if the goal is Data as a Product and Monetizing data — how this strategy will help and if the idea is to bring more value from Data towards the Business — how it will help etc.
4. The When: Establish a clear timeline and define milestones and by who the activity should be complete and provide clear definitions on how this activity can benefit the organization.
The What: Financial Justification on the Data Activity and how the organization will benefit from it.
As you have innovated effectively, now your organization is ready to Transform and become a Modern Data-centric Organization.
Transform
Till here, everything is on paper with few building blocks and capabilities are created to ensure that the Transformation takes place effectively. This is the Execution / Implementation phase where we use the capabilities to Modernize the Data Platforms and to build a Data-centric Organization. Once you have completed this step, you have “made a Data-centric organization, a modern one”.
Implementation can happen via in-house or outsourcing. Define working groups and squads / hives such that the empowered set of Data Teams can be champions and help other Domain teams to build and modernize Data Platforms.
Next: Define a good Modern Data Technology Infrastructure
