Developing an analytics roadmap is an essential part of your analytics strategy. In this post, we’ll tell you what you need to know before you start building your roadmap.

 

A robust analytics strategy doesn’t happen by chance; neither does the analytics roadmap that will get you there. We know; at Absolutdata, we’ve set up many roadmaps in our time. So, let’s talk about what you need to consider before you build your analytics roadmap – a roadmap to the roadmap, if you will.

 

What Makes a Good Analytics Roadmap?

Data analytics isn’t a proverbial island; it requires the right blend of people, data, products, technology, process, and governance to be successful and productive. Similarly, an arrow-straight roadmap that focuses solely on the technology and skills needed will not work.

An analytics roadmap needs to start with a comprehensive review of the business situation – understanding the business goals and ensuring alignment with them. Part of this review should also include an audit of any existing analytics usage/tools/infrastructure in your organization.

Next, the roadmap should define the actions and strategies that will be taken to meet this goal. These will almost always be done in phases, so prioritizing the steps of the implementation process is also part of a good analytics roadmap.

 

Why Bother with an Analytics Roadmap?

A purposeful and organized rollout is always more efficient and effective than the alternative. When you’re implementing a change across an organization of any size, it helps to coordinate activities across business functions and capabilities. But developing an analytics roadmap does more than align technology and business initiatives and help strategically plan for business needs. It also allows you to:

  • Evaluate data from a broader, more strategic perspective.
  • Provide for quick wins as well as long-term strategic opportunities.
  • Deliver incremental value while mitigating certain risks.

Properly constructed, an analytics roadmap details how you can create impact across business areas, including:

  • Research and Development
  • Risk management
  • Product innovation
  • Portfolio management
  • Demand and market forecasting
  • Consumer behavior and engagement
  • Spend optimization and resource allocation
  • Field-force effectiveness
  • Supply chain planning and network optimization
  • Competitive intelligence

 

Mapping Your Roadmap with Design Thinking

So, now that we know what a quality analytics roadmap looks like and why it’s so important, let’s get down to the planning stage. What process should you expect when you’re delivering a roadmap?

We’ve found that borrowing a page from design thinking – and keeping an agile mindset – is very effective when building out an analytics roadmap. The five-step process framework we follow looks something like this:

Image: ©Absolutdata
Image: ©Absolutdata

At this point, you’ve already set your vision and direction (i.e. identified goals, set objectives and expectations, communicated with key stakeholders, etc.) and done your health check (i.e. your evaluation of the current state of analytics in your company). You have a clear idea of where you are and a direction in which to travel. You know the end goal, and you have a path to take you there.

Now it’s time to ideate. Start creating detailed plans, identifying opportunities within your organization where analytics can be deployed and looking for options that will help you meet your goals. This is where you can begin to move into details.

If you’re familiar with design thinking, you know that after ideation comes prototyping – the chance to try out ideas and see if they work. For analytics, prototyping often means embracing lean strategies. Getting a pilot project going and seeing how it performs in a limited area is a great way to see what works and what doesn’t.

The word ‘prototype’ implies that this is far from a finished product. It helps to think of design thinking (and of rolling out analytics) as a cycle rather than a linear process. It’s normal and even beneficial to iterate through solutions and create new ideas as new insights come in.

Eventually, you’ll hit on an analytics roadmap (and an analytics setup) that matches your goals. This is where agility comes into play; it allows you to build the prototype solution (i.e. your analytics setup) in a fast, incremental way. You can adjust course and deliver precisely what your company needs.

 

You’ve Got Your Analytics Roadmap. Now What?

Once you get your analytics roadmap, what’s next? First, the rollout process will proceed in a more orderly manner; that’s a given. But the positive effects of a well-planned rollout go much deeper than the initial process; you can also experience analytics-led improvements in productivity on a wider scale, such as faster decision making (made possible by integrated reporting). You’ll also be on your way to that holy grail of modern business: digital transformation and its accompanying new business experiences, models, culture, and change management.

So, is it worthwhile to spend the extra time planning your analytics roadmap? You can decide for yourself, but we think it’s all worth it!

Authored by: Dr. Anil Kaul, Co-founder and CEO of Absolutdata

Subscribe

 

Related Absolutdata products and services: NAVIK AI PlatformAI & Data SciencesMarketing Analytics