Our analytics team supports a broad set of services from data strategy and modern data architecture, to governance, master data management, business intelligence, data engineering and data operations, all the way through machine learning, AI, and predictive analytics. We also understand that our clients who are in the beginning of their journey toward doing complex analytics may not have the resources for all these concepts and roles, which is what inspired the Analytics Activation service. Our Activation program will jumpstart analytics at your organization, using templates and checklists at every stage of a guided project to upskill your team and formalize the journey.
It is important to understand a few things to set the scene of the Activation journey:
- Digital transformation can’t happen without Data + Analytics – The difficulties of 2020 created an urgent need to succeed in a digital world. Data is the backbone of digital; it is the virtual representation of real-world scenarios that we can use to do business. And analytics is a vehicle to drive competitive advantage with that data.
- These capabilities don’t develop overnight – Transformation takes time and growing new skills across the enterprise will take time and will require change management.
- Unicorns are hard to come by – hiring a single data scientist with the expectation that they’re going to fill all the roles we further discuss below is nearly impossible. It takes a multitude of roles to build up your analytics capabilities with all the necessary support functions.
The activation program aims to vet the capabilities of your organization to build data products. The program walks through each step of a pilot project, with a keen focus on evaluating processes, technology, integrations, and skills required to deliver Data Products. This method will identify gaps and make improvements each project, gaining momentum and fostering organizational adoption along the way. An overview of our project delivery methodology is below:
The intended outcomes of this process are to deliver value to the business and partners and develop and grow important capabilities. Establishing analytics within an organization requires many roles and skills. As evident in the below visual, different roles are necessary at different points of the project. It should be noted that while these roles are the star of their relative stage, many of these roles play a part throughout the entire project.
Do any of these barriers sound familiar to your team? These are all barriers that will hold the organization back from delivering scaled analytics value.
- Limited focus on Master Data Management / Governance
- Over-reliance on qualitative, ‘gut feel’ decision-making processes
- Out-dated, disconnected tool-sets and technology landscape
- Inability to derive or leverage insights in a timely fashion
- Organizational models and business processes that preclude insights sharing and x-functional collaboration
Now let’s get into what actually makes up the Activation Program so the above barriers can be alleviated in an organized, purposeful manner. It can be broken down into three high-level phases:
- Initiate and Data Plan: The team will have a business value workshop to choose an initial use case for the proof of value project, define success and end goals, and begin the more tactical planning steps like creating analysis plans, data gathering, and training on new roles and responsibilities within analytics.
- Model Build: In this phase, it is first necessary to profile and understand the data sources at hand and align with business analysts and business translators on any data clean up decisions. Then the team can begin and progress on the predictive model and spend, and spend ample testing and refining the model to move towards optimal results of the model.
- Scale + Deploy: This exciting phase will enable future success for the proof of value project! The team will work to set up data pipelines and build an output like a tool or dashboard for end-users to interact with generated predictions or insights. Rounding out the phase, build momentum in analytics through knowledge transfer activities and sharing successes throughout the organization.
Why are proof of values projects so important to standing up analytics within an organization? The answer is rooted in establishing a quick win. Getting analysts hands on to a new tool as quick as possible, in addition to gaining executive buy in throughout the whole project life cycle familiarizes those of all levels on what makes an analytics project successful. The key to success in analytics is ensuring action can be taken from the efforts. A clear project scope with a direct use towards business goals provides positive results, easing change management throughout the organization. Additionally, building momentum in continuing to do analytics projects after the initial proof of value will keep expanding the reach and positive impact analytics can have throughout various points in an organization.
To summarize with an example, let’s take a client we call the Activation Blueprint. Looking back two years after the initial activation, we see a few themes propelling the successful data science outcomes and organizational buy in. First, client curiosity and connectedness to the business. The key stakeholders are knowledgeable on both analytics and the business and are seamless fits as business translators. Every finding we bring forward sparks new ideas from the business and questions to go after. Additionally, the business drives the priority of backlog, meaning that the analytics work is always valuable and not something the team runs with on their own and ends up misaligned. We’ve seen companies struggle with drifting into the realm of curiosity with analytics where there may not be direct business applicability to work completed. Finally, the analytics team at play is diverse in skillset – with business analyst and requirements gathering capabilities, all the way through the more technical elements of data science – this diversity all things necessary for continuous delivery of analytics. The team started with one analyst and one manager and grew to meet business need, sustaining successful delivery over the last two years.
For more information on Activating Analytics and client examples, you can find a recap of our webinar below.