This is part 1 of a multi-part series on the Analytics Operating Model.

The rapidly changing big data landscape is driving organizations to scrutinize data more carefully, as a way to tackle their most challenging problems. From climate change to healthcare, a recent article in Data Informed explored “How Big Data and AI Help Us Tackle The World’s Biggest Problems in 2017 and Beyond”. While the author stopped short of making a case for analytics creating world peace, the headline speaks to the aggressive transformation underway in the analytics space and how it will impact the world around us.

Rewind to 2016. Literature at that time indicated that the focus of the year was centered around ‘micro analytics’, where small pieces of contextual data deliver actionable insights. In just a year’s time we have seen a shift in thinking from a “micro-level” to leveraging the power of analytics to “tackle the world’s biggest problems”. This step change results in a growing urgency and pressure on organizations to quickly evaluate and mature their analytic capabilities, however the transformation should not be started without giving great consideration to how analytics can integrate and provide value to the enterprise.

 

 

 

Figure 1: Analytics Operating Model – Key considerations to develop and mature analytics capabilities

Before moving into the dynamics of the operating model, we must first set the vision and strategy for the analytics team. The vision and strategy set the tone for execution and establish the parameters to guide each core element of the operating model and the required analytics maturity that we will explore in more depth throughout this series:

A helpful way to think about strategy was outlined by Hambrick and Fredrickson in their Strategy Diamond. They view an effective strategy in five parts with each addressing a key question:

  • Arenas: where will we be active?
  • Vehicles: how will we get there?
  • Differentiators: how will we win in the marketplace?
  • Staging: what will be our speed and sequence of moves?
  • Economic logic: how will we obtain our returns?

Through this framework, you can begin to see how the answer to each question will impact the analytics operating model. Funding options, capability sourcing (insourcing vs. outsourcing), technology platforms and roadmaps all need to be considered, to determine how analytics will be enabled within the organization. This framework should drive the required capabilities, tools, and processes. However, rarely do vision and strategy precede need; that is, many executives and leaders look for results without knowing what strategy is needed to reach those results. So what should be done – what really delivers value from analytics pursuits, and how do you course correct before it’s too late? The solution centers around an effective Analytics Operating Model.

As we continue this seven-part blog series, we will share first-hand insights into the challenges of managing analytics projects; key processes that enable value realization; the people who will be impacted; and the ever-changing technologies that are needed to make it happen. Over the next several weeks, we will explore:

  • Vision & Strategy Clear vision & strategy for funding, capabilities, and technology
  • Governance & Organization Structure Streamlined processes and organization
  • Talent & CapabilityAnalytics capabilities, talent sourcing and development
  • Analytics ProcessesAnalytics processes to deliver products & services
  • Architecture & TechnologyRequired technology and data platforms
  • Analytics Data ManagementProactive management of the data lifecycle
  • Capability Maturity ModelProgression of analytics maturity across each core element

The analytics journey is moving through uncharted territory, and we invite you to share your experiences and questions with our team as we walk through our Analytics Operating Model. Whether your organization is just beginning to consider analytics or is mature in practice, the evolving landscape requires constant adjustment to the operating model to remain relevant and “tackle the world’s biggest problems”.

In our upcoming blog series, we will explore the key elements for developing and maturing analytics capabilities within any organization. We will delve into each element within the Analytics Operating Model, to explain how they work in tandem. The resulting solutions can cut through the masses of data to produce valuable, actionable insights.

 

Click here to learn more about our Analytics & Information Management practice. Want to continue the conversation? Contact us at insights@enaxisconsulting.com, and continue to follow this series as we dig deeper into each element of the Analytics Operating Model.