CDO Advisory / Data Strategy and Execution
A data strategy is developed to overcome the challenges identified in an organization's business strategy and mission goals. A good data strategy comprises of a set of policies and actions, to overcome difficult challenges the organization is facing. At AlyData we develop the "kernel" or the core of the strategy and an execution plan. The "kernel" has three components: (1) Diagnosis (problem definition or the nature of the problem), (2) Guiding Policy (what's our basic approach and decisions), and (3) Coherent action (what are we going to do?).
Data leaders are tasked to execute the data strategy. They use their domain expertise and relationships to break down data silos and unleash the power of data by deploying artificial intelligence solutions to enable innovation, new product development, and driving bottom line results. AlyData's Data Advisory Service, Data & Analytics Strategy Framework and the Vision, Organize, Innovate, Change, and Execute (VOICE) methodology were launched to assist data leaders achieve their mission.
AlyData's article on Medium co-authored with the CDO of TDAmeritrade titled "Co-created Data and Analytics Strategy to Deliver Business Success" - Click Here
Our four major contributions to the Data and Analytics Strategy Discussion are:
First - A Data and Analytics strategy must be co-created with the business partners — to ensure that it aligns with and supports the business strategy. After base lining the initial Data and Analytics Strategy, business and data and analytics teams need to come together on a regular basis to ensure that the connections between the desired business outcomes and data and analytics initiatives are always aligned and accretive to the organization.
Second — Each of the six capabilities of the business outcomes value chain must to strong to generate the desired business outcomes.
Third — Organizations will have to introduce a new role — that of a Data Economist to develop the value proposition and the return on investment metrics.
And finally — cross-functional engagement is required to drive the data and analytics strategy and ultimately a data-driven culture.
Data Strategy & Execution
Data Management Maturity
Typically, Big Data projects are launched to augment existing data stores and infrastructure. AlyData advisors review the existing data architecture and major pain points - to gain an understanding of the current state, before embarking on the creation of a Strategy and Execution Roadmap that will unlock data silos and enable critical insights. AlyData experts will train executives and staff on how to utilise the insights gained to gain a competitive advantage and achieve their mission.
During this process, AlyData advisors use project accelerators such as Architecture templates, questionnaires and data profiling utilities.
In order to succeed in their roles, CDOs must stay abreast of the latest developments in the fields of data management and analytics. AlyData's leadership is comprised of industry thought leaders in data management and analytics. We regularly publish books and articles on data-driven leadership and are able to deliver highly customized content and advisory services to our CDO clients, coupled with our strengths in developing detailed roadmaps and execution plans.
What are the key trends, challenges, and opportunities with respect to data management, analytics and data science that may impact your business and influence your strategy? AlyData's industry research team culls this data through content analysis, survey results, and tapping into our Subject Matter Experts to provide perspectives and insights. These resources will help you answer the questions: What is the current industry trend related to data management, analytics, and data science? What are your CDO peers doing with respect to technology investments? What are your major companies/competitors in the industry investing in and why? How will machine learning and Internet-of-Things impact your business? What can you do to leverage open source tools to reduce costs and maximize productivity? etc.