In addition, we have many years of exposure to the business issues faced by early stage technology companies. We focus on providing a professional and reliable assessment of the company’s technology and the team’s ability to deliver. This allows investors to focus on the all-important aspects of examining the company and the management team and agreeing suitable terms

Capital investment and venture capital and seed money,first round, start-up, venture, angel investors need to assess and determine whether a technology company has real and scalable technology to invest in.  Can you company get your new technology to market?  How will your technology compete in the market.  Does your company have a solid business plan and go to market strategy?

How do you demonstrate or prove to investors that your company technology is going to be successful and profitable and a value to their financial investment?

Can a company provide a documentation portfolio that would be required to convince investors?  Can investors hire a technology consultant to perform analysis, assessment and due diligence on a technology company they want to invest in?  How do we limit our risk to value proposition?

How do we identify our internal weaknesses and vulnerabilities that would prevent capital equity financial venture investment start up funding, early-phase development, early stage investments

Can a technology investment be profitable, how do we know the technology is real, good, and marketable?

Can a technology assessment help us find venture capital and investor funding?

  • Customers must enter our evaluation portal and complete both a “Needs Assessment” and a “Readiness Assessment”, which allows us to identify customers with potential for success:

    • The Needs Assessment focuses on the organization’s purpose and needs for developing a Data Science capability, and the alignment to their existing technology roadmap and internal strategic planning objectives.

      • These needs should be aligned with existing/emerging organizational goals, objectives and priorities.

      • These needs should be commonly understood/supported at all levels of the organization.

    • A Readiness Assessment looks more specifically at the engagement of the organization: 

      • Is this a technology project (bottom-up)?  An executive declaration (top-down)?

      • Does the initiative have both top-down (executive/mgmt.) and bottom-up (technology) support?

      • Are there foundational artifacts of Enterprise Architecture already in place?

        • IT Governance

        • Data Governance

        • Data Models, Data WH, OLAP, Lakes

      • Does the organization have the required infrastructure to support Data Science?

      • Does the organization have the required skills and resources to support Data Science (aside from technology skills): i.e. analysis, statistics, maths, and social sciences?

      • Has the organization solved their issues of ETL, data normalization, data harmonization, data quality and privacy/security?

      • Does the organization have data science skills

 

 

  • Most data science/big data projects fail (up to 85% per Gartner).

  • Most failures are due to lack of planning, lack of focus on purpose and application, and because of the struggles of getting meaningful, complete and clean data into the data science platform

  • Most organizations struggle with data integration, and seek big data tools to circumvent the difficult work of integration, data cleansing, data normalization and enterprise metadata.

  • Too many industries are buying into Data Science from the top-down (purchase a specific product or technology, without strategic alignment to the existing organization, current goals, objectives, skills and infrastructure).

  • Too many industries are buying into Data Science/BI Tools to analyze their own customer data and behaviors, however they have not first established a sound CRM application, with multi-channel next gen web platforms, and effective Master Data Management (MDM).

  • Early adopters are too often looking for new ways to get answers from their application data, only because they have been unsuccessful with conventional reporting and analysis tools.

  • Many organizations are led down a “primrose path” by vendors of DS Products, over-simplifying the use, operation and data population of said systems.  Like most application vendors, the issues of data migration and data integration/ingestion are treated as insignificant afterthoughts of a DS project.  Most often, selling their wares on the notion that their algorithmic tools will “make sense of the data” magically.

    • One-off data feeds and interfaces (often scripts using XSLT) are NOT “loosely-coupled” but instead brittle,  with respect to maintenance.

    • Direct data dumps or feeds to a proprietary analytics tool are unknown, unmanageable and non-reusable without assistance from the vendor

Methods:

Essential IT Strategy Services are the paramount foundation of both our pre-qualification process, and our professional service deliverables.  The first stage of any/all projects is re-visiting and testing the project strategy alignment.  Project Strategy Alignment is about making sure that a project follows a vision for success.

  • Alignment is about ensuring that the project manager, project team and selected vendor(s) are on the same page from the outset of the project with the business sponsors and stakeholders of the organization

  • Successful alignment avoids conflicts and ensures project delivery in in line with business expectations, goals and strategic business objectives

  • Alignment begins with a shared vision among stakeholders, and a process for gaining all of the necessary buy-in (organizational/motivational models) and establishing clear roles and responsibilities within a structured governance model

  • Alignment is about specifying factors that will ensure project success, as well as their corresponding measures, risk assessments and mitigation strategies

A helpful tool for realizing the detailed expectations of an implementation project is to develop a Concept of Operations (ConOps).   The ConOps serves as the conceptual “User Guide” for the new system being implemented, including:

  • What will this system do?

  • How will this system operate?

  • What will this system look like?

  • How will it benefit the organization?

  • What will such a system Cost? Value? ROI?

The ConOps addresses the concerns and perspectives of all system owners, users, developers, both business and technical, and all stakeholders from administrative/executive levels to the operational/line staff.

Data Science Program Charter

  • Mission, Vision, Goals and Objectives

  • SWOT

  • Assumptions/RACI

  • Desired Outcomes/Performance Measurement

  • Functional Requirements

  • Build vs Buy Analysis

  • Concept of Operations:

  • Motivational Model – Why?

  • Organizational Model – Who?

  • Conceptual Model – What?

  • Logical Model – How?

  • Physical Model – Where?

  • Operating Model

    • Governance Model

    • Communication Plan

Enterprise Architecture

DataAdaptiX

 

The fundamental characteristics of Enterprise Architecture (EA) can be described as follows:

  • EA is a holistic approach to documenting and managing an enterprise’s current and future states in terms of strategy, business processes and technology.

  • The adoption of EA can enable enterprises to make informed decisions and to implement the decisions as efficient as possible.

  • In governance, an EA program needs to address the dynamic and political nature of enterprises thereby making EA a pragmatic, organizational exercise.

  • The distinction between making decisions and implementing them is especially important from a strategic perspective. This stresses the dual purpose of EA to enable enterprises to:

    • Do the right things (strategy)

    • Do things right (operational effectiveness)

Purpose of Enterprise Architecture 

The purpose of EA is the greater alignment between IT and business concerns. The main purpose of enterprise architecture is to guide the process of planning and designing the IT/IS capabilities of an enterprise in order to meet desired organizational objectives.

Benefits of Enterprise Architecture 

The enterprise architecture benefits include: more efficient business operation with lower costs; more shared capabilities; lower management costs; more flexible workforce; more organization; less duplication and redundancies; and improved business productivity.

Benefits of Adopting an EA Framework

An enterprise architecture framework (EA framework) defines how to create and use enterprise architecture. An architecture framework provides principles and practices for creating and using the architecture description of a system.  Examples include TOGAF, DoDAF, FEAF, and Zachman.

Benefits of Adopting the TOGAF Framework

An effective Enterprise Architecture can bring important benefits to the organization. Specific benefits of an Enterprise Architecture include:

 

-More effective and efficient business operations:

  • Lower business operation costs

  • More agile organization

  • Business capabilities shared across the organization

  • Lower change management costs

  • More flexible workforce

  • Improved business productivity

-More effective and efficient Digital Transformation and IT operations:

  • Extending effective reach of the enterprise through digital capability

  • Bringing all components of the enterprise into a harmonized environment

  • Lower software development, support, and maintenance costs

  • Increased portability of applications

  • Improved interoperability and easier system and network management

  • Improved ability to address critical enterprise-wide issues like security

  • Easier upgrade and exchange of system components

-Better return on existing investment, reduced risk for future investment:

  • Reduced complexity in the business and IT

  • Maximum return on investment in existing business and IT infrastructure

  • The flexibility to make, buy, or out-source business and IT solutions

  • Reduced risk overall in new investments and their cost of ownership

-Faster, simpler, and cheaper procurement:

  • Buying decisions are simpler, because the information governing procurement is readily available in a coherent plan

  • The procurement process is faster - maximizing procurement speed and flexibility without sacrificing architectural coherence

  • The ability to procure heterogeneous, multi-vendor open systems

Why is adopting Enterprise Architecture important to our organization?


The ability to secure more economic capabilities