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Data driven ready step 2 - Team

When you have formulated and gained approval, strong support and buy-in for your datadriven strategy, you will need to form a team to help you achieve your objectives.

As with all knowledge based initiatives it is critical to the success of your program/project that you find the right persons with the right set of knowledge and experiences. You will also need to decide upon which concept to use when it comes to how you would like to, or have to, organise your team. In some cases/organisations it is better with a centralised team that can assist or do all the work, whereas it in some organisations is required or preferred to have a decentralised team operating within the existing organisational structures.

All this is important for the success of your data driven initiative and that is why we have established ”Team” as the second step in our ”Data driven ready model”.

Crystal clear and undoubted mandate

As we have already touched upon in previous blog posts, it is important to have sufficient support for your initiative in order to be successful. This requires a crystal clear and undoubted mandate from C-level executives. Once this is established you will need to establish the team that is supposed to deliver on the expectations and promise of a Data driven initiative.

First of all you need to decide on how to lead the the program/project. This includes the actual individuals in charge of the program, but also how to steer and follow up on progress (we will expand on the latter further down this blog post). As for leadership you should aim for an individual/individuals that ideally has previous experience from a similar initiative.

As this is a fairly new area, it might be hard to find persons with the exact right profile and experience from data driven implementations, but you should definitely look for individuals that has experience from running complex transformation projects within digitization before. This person(s) should also have the ability to communicate with both top management (C-level) and other parts of the organisation to be able to communicate progress, what is required and why, etc…

The right leadership for your initiative significantly increases the chances of success. If you can’t find the right person internally, look for an external resource to fill the role, or do it in tandem with an internal resource to ensure knowledge transfer and the right anchoring within the organisation. 

Data Analytics and Data Science

Your team will of course require expertise within the specific field of Data Analytics and Data Science to meet the targets of your initiative. This knowledge will probably have to be recruited externally to start with (either as consultants or new hires), as most organisations do not have this knowledge internally already.

Even though it is probably required to utilise external resources to kick-start your Data driven initiative, you should in parallell define a strategy to gain the required resources to develop and maintain your initiative over time in an efficient manner. How you choose to do this is of course up to a number of different factors, such as your organisations strategy when it comes to maintenance of digital initiatives, the ability to allocate internal resources and so forth.

However, both the short and long term staffing/resource allocation to support your initiative should be on the agenda early in the process. Depending on the chosen strategy for this, you will then have to create a plan to ensure resources have the right skill sets and competence over time.

This plan should include coaching guidelines, training and introduction to ”real-life” assignments with sufficient support. Rightly managed you will be able to create a strong team that helps you deliver a successful initiative and contribute in making your organisation data-driven ready.

DDCC – Data Driven Competency Center

As you have established a plan for how to recruit and train the right person with a relevant skill-set, you will also have to decide how to organise the resources. There are different options here. You can choose to run a centralised team that is responsible for the whole initiative and does all the actual work as a kind of ”internal consultants”. This team could be compared with an ”ICC – Integration Competency Center”, which has often been used in implementations of SOA (Service Oriented Architecture) related to APIs and systemintegration. Such a team in this context could potentially be called a ”DDCC – Data Driven Competency Center” or similar to identify the purpose and objective of the team.

This form of organisation is beneficial if you want to give a specific unit a clear mandate and responsibility for an initiative like this. To make this kind of organisation successful, you will need a very clear mandate to do what is necessary and the team will definitely need the support of management to be able to allocate resources and make a difference in the larger organisation. Another approach is to work with an ”embedded organisation”.

This means that you will work only with a smaller central team to build principles, guidelines, training plans etc to support the initiative – something that may rather be identified as a ”Center of Excellence/Enablement”. The actual work will be performed by resources that are embedded in the existing organisation.

You can identify ambassadors in relevant departments or business units that you can train and educate on the benefits of a data-driven approach and they can then in turn identify use cases in the respective organisations and implement these. This approach is perhaps less provocative in some organisations as you will not need to mandate and finance a large central unit that is supposed to tell the rest of the organisation what to do.

With the decentralised approach you will also have the advantage of people already in the organisation being active with finding use cases and acting as ambassadors for the initiative if they are successful. The chosen organisational model is depending on the pre-requisites of your organisation, but we can guide you based on our previous experiences.

Choosing methodology

The last consideration when it comes to team and organisation is to choose which methodologies to use to follow work and progress. In this context popular methodologies such as Kanban or Scrum can be used, with work divided in shorter or longer sprints based on your organisations requirements.

You can also choose to incorporate this work in your existing day-to-day operations as an activity that will be followed up according to existing routines. There are benefits with each of these models and the chosen approach will have to be sync with how you want to run the initiative and how you choose to report progress and incorporate the team in the existing organisation, or not. 

We will return more specifically to which roles and what kind of competencies they will require in later blog posts, so stayed tune and keep reading for more information on our view on roles such as Data Scientists, Data Engineers, Analytical engineers, BI developers, ML engineers and others.

More information

Redpill Linpro is launching our Data driven ready model in a viral way by releasing a series of blog posts to introduce each step in the model. This is the third in this series. Below you will find a little ”sneak-peak” into the different steps of the model. Stay tuned in this forum for more information on how to assure Data driven readiness...

Data driven model
Written by Fredrik Svensson