Putting together a roadmap to guide your Data & Analytics journey

By Chris Kearns, Regional Manager, Altis UK

 

Consider the following four scenarios and ask yourself which is closest to your organisation:

Scenario 1: Your organisation relies on an army of people to manually create a mountain of spreadsheets/PowerPoint slides to provide information to support decision making. Different people create similar siloed reports that don’t support cross-departmental reporting and there are many arguments about the accuracy of the data or whose data is “right”.

Scenario 2: Your organisation has introduced a toolset to help with the process of creating dashboards to support decision making, but it’s still a manual process controlled by key people. The dashboards are often focussed on a single area of information (reporting silos) and don’t necessarily support cross-departmental needs. There are still arguments about the accuracy of the data or whose dashboard is “right”.

Scenario 3: Your organisation has gone down the path of trying to centralise and automate the collection, storage, and governance of data to support decision making. However, they’ve only succeeded in bringing in a single data set or two and now there are arguments about which data sets should be brought in next or which tools should be used to visualise the data. There is no plan to cater for cross-departmental measurements. Tired of not being treated as a priority, departments (such as HR or Finance) or teams have decided to implement their own reporting solution, further exacerbating the problem of reporting silos.

Scenario 4: Your organisation is also on the path to centralising and automating the collection, storage, and governance of data to support decision making as per scenario 3 above. There is organisation-wide support for the roadmap governing the delivery of the solution. The roadmap factors in cross-departmental measurements, aiming to eliminate reporting silos. The overarching steering group is comprised of representatives from across the organisation and they have agreed the priority order in which data sets will be delivered by the roadmap. The steering group has the autonomy to change the roadmap priority order as and when business priorities change. Each priority stage is being delivered as its own phase and the value is being realised incrementally by the business. As each phase is released, competing sources of the same information are decommissioned so that a single source of the information is available for reporting and analysis. Easy to understand business descriptions of the data exist to minimise misunderstandings about the data. The indicative costs of each step of the roadmap are known and agreed up-front. Progress against the roadmap is measured and reported at regular steering group meetings.

The above represents data maturity increasing from one scenario to the next.

How can you increase your organisation’s data maturity without having to go through the painful intermediary stages? Putting together a roadmap to guide your Data & Analytics journey will get you started on the right path.

This blog will discuss the Altis approach to developing a Data & Analytics roadmap based on the successful delivery of over 55 such engagements across a variety of organisations in the UK, Australia and New Zealand.
 

Strategy & Roadmap Approach

There are seven key steps in the Altis approach to delivering a Strategy & Roadmap engagement as outlined in the diagram below.

DA Strategy

  1. Project kick-off – The project kick-off meeting is the prime opportunity to get the engagement started on the right note. This meeting covers: ensuring that key stakeholders understand the project approach; agreeing the project goals and purpose; agreeing stakeholder roles and responsibilities on the project; agreeing what is in and out of scope and what will be delivered; establishing project success criteria; shaking out and addressing any questions and concerns; identifying any detractors so that the negative impact they may have on the project can be mitigated.
  2. Educate on principles – This involves getting the project stakeholders together to build a common understanding of terminology for project interviews and deliverables. This is important as it provides everyone with a “Data & Analytics 101” lesson, which helps establish common terminology. It’s also another opportunity to help manage expectations as to how the project is going to be conducted and what will be delivered. Ongoing informal education throughout the project is also important to ensure that everyone remains clear as to the project goals and the path to achieving them.
  3. Review current state – It is important to understand the current state of Data & Analytics before delving too deeply into business requirements for a future state. This will help to understand what is feasible from a data perspective before engaging too heavily with the business, as well as to understand if there is anything of the current state that can be leveraged for the future state of Data & Analytics. The current state review aims to look into current infrastructure and software, current data sources, current reporting and analysis systems, current data governance, and any previous relevant project collateral. A current state diagram provides an easy to understand overview of the movement of data from source through to consumption from a Data & Analytics perspective.
  4. Gather business requirements – This step commences after Review Current State because we need to understand enough about the current state in order to engage with the business in a more informed manner. E.g. Understanding the limitations of the existing source systems will help us manage expectations if the business asks for something that doesn’t exist from a data source point of view. The loop-back to Review Current State in the diagram recognises that gathering business requirements will invariably raise questions about the current state, which will need to be further analysed. Gathering business requirements involves communicating the requirements gathering approach to stakeholders prior to workshops, booking in and conducting the requirements gathering workshops and capturing the requirements (including governance and toolset requirements) in an efficient and meaningful way, and then distilling those requirements into a format that makes it easy for stakeholders to comprehend.
  5. Define future state – Once the current state is understood and the business requirements have been gathered/analysed/confirmed, we will be in a position to define the future state of Data & Analytics. A future state diagram is the primary means to communicate the future state vision. This diagram will illustrate the flow of data from source systems through to Data & Analytics systems. If multiple options are being considered, then a recommendation will be provided. The future state of data governance should also be considered here. This step is also the appropriate time to consider the assessment and recommendation of a data platform and toolsets if this is in scope for the engagement.
  6. Design path to future state – We are now at the point where we understand the current state and have a clear view of the future state Data & Analytics vision. The purpose of this step is to design a roadmap that will take the organisation from the current state to the future state vision. The future state Data & Analytics solution will need to be delivered in a series of phases. The scope and nature of each phase will begin to crystallise during the requirements gathering step. A workshop will be held with key stakeholders to agree prioritise the phases. The roadmap needs to include indicative pricing for each phase to give the organisation a sense of the overall cost to feed into the business case. The proposed roadmap resourcing model and ongoing operational model needs to be considered at this point too.
  7. Document and deliver roadmap – The final step of the engagement is to distil all of the deliverables from the above steps into a consolidated Data & Analytics Strategy & Roadmap presentation for delivery to the steering group and any other key stakeholders. The presentation will include the following: Current State Assessment, Business Requirements, Future State Recommendation, Roadmap broken into prioritised phases, and Roadmap Estimates. The presentation will highlight any anticipated issues and risks, as well as any pre-requisites or dependencies including any likely impact on existing and related projects/resources. There should be no surprises in the final presentation as the project steering group will have been fully engaged during the project and will have had direct input on key aspects of the roadmap.

 

Lessons Learnt

We’ve learnt a number of key lessons from delivering over 55 Strategy & Roadmap engagements. Here are six to consider:

  1. A Strategy and Roadmap project is a business driven engagement, with IT as a key partner.
  2. A strong and influential executive sponsor is required along with a motivated steering group comprised of influential change agents.
  3. A well respected, experienced, influential, and organised business champion with strong data knowledge is a key asset to the project.
  4. The steering committee needs to represent all key parts of the business to ensure there is buy-in and to prevent the “my department/team wasn’t consulted” excuse down the track.
  5. Markets shift, business strategy changes, business priorities change, technologies shift, etc. Therefore, the roadmap cannot be fixed in stone. It is important that the roadmap and the steering group governing it remain open minded and adaptable.
  6. Manage expectations along the way. Golden rule: no surprises at the end!

 

Conclusion

This blog summarises Altis’ proven approach to developing a Data & Analytics roadmap that in turn helps organisations attain a higher level of data maturity. I described a scenario 4 organisation as having the highest level of data maturity. What distinguished them from the other three scenarios was the organisation-wide support and execution of a Data & Analytics roadmap.

According to a Japanese proverb (supposedly), “Vision without action is a daydream, action without a vision is a nightmare”. Put in our words, A roadmap without action is a daydream, action without a roadmap is a nightmare!

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