Designing and implementing a modern data strategy for a business is a complex task that if done well will transform the value of data held by a business significantly and result in step change workforce productivity gains.
We aim to help our clients build a modern data strategy by applying our Consulting service to the data challenges that modern businesses face. Our Consulting service is the starting point to achieve this, its ultimate goal being to help our clients build a data strategy that can be implemented at their pace and ensure their valuable data assets are managed efficiently and with maximum return on investment.
The Data Business Consulting service consists of 6 steps which are outlined in summary below:
1. INITIAL DISCUSSION
This is a discovery phase that allows us to understand a business, its goals and its challenges related to data. This discovery will provide valuable insight that enables us to tailor each step within our Consulting service to specific business needs.
2. TARGET DATA MODEL DESIGN
This step is about building a client’s target end state data model inclusive of data sources, processes, technology and governance. The output will be a target data model for the client’s business and it will represents a core component of the overall data strategy.
3. CURRENT STATE ANALYSIS
This step focuses on a client’s existing data-related business processes, technology capabilities, policies, governance and data sources. The purpose of this phase is to understand the current playing field and ultimately provide an aid to identify the activities required to move from the current state to the target end state, as defined by the data model. Note steps 2 and 3 are likely to progress in parallel.
4. REQUIREMENTS CAPTURE
Once we have established the current state and desired end state positions we can identify how to move from the as-is position to the to-be position. By analysing the two states we can identify gaps across the data models and capture these in a requirements document.
We would then seek input on these requirements from relevant business stakeholders to obtain buy-in and ultimately sign off on the proposed changes. The sign-off stage is essential to avoiding confusion across stakeholder groups and producing an inclusive change agenda.
5. DATA STRATEGY EXECUTION PLANNING
The creation of a Data Strategy Execution Plan is vital to the successful delivery of the data strategy. The plan is essentially the collection of all the detailed activities, resources, timelines and costs grouped together into a structured view so that start and end points can be visualised. It is likely to consist of two plans, a tactical quick-win plan and the longer-term strategic plan. Key inputs to this stage are the data model and the requirements documents created in steps 2 and 5.
6. STRUCTURED CHANGE MANAGEMENT
Implementing the Data Strategy Execution Plan will deliver the new data strategy and data model that will change the client’s approach to the desired specification. This step is complex as it is may encompass organisational change, cultural change, technology change and changes in business processes. In addition, data governance, which deals with overall management of availability, usability, consistency, integrity, and security of data may also need to be overhauled.
If the implementation is not conducted using a structured change management process the required changes are likely to be delivered in silos or not at all, the end result being a poor copy of the envisioned data strategy for the business.
Therefore, in this step, we will leverage our structured change management processes to ensure that the appropriate project management delivers the best possible outcome.