Three must-make investments in data analytics

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Data analytics. Much said. Much done. But are you getting the returns you want? As organisations continue hopping on to the digitisation bandwagon and upping their data and analytics investments, the big question is: Are you doing what you need to get what you want?

With so much focus on data, analytics and digital innovation, companies across geographies, industries and functions are still struggling to realise and measure value from their analytics investments. And why so? We are not precise about our planning, implementing and measuring. Quite a blanket statement this is, but true. So if you keep in mind three things while doing the above (planning, implementing and measuring), you can stay ahead of the herd.

First, align your analytics initiatives with the culture of your organisation. True transformation is all about creating an organisational culture based on data analytics. To build such a culture, it is essential that all relevant stakeholders are involved, particularly the senior management. And one good way to start is to invest in a large-scale collaborative visioning exercise right at the beginning. Initiatives selected through such visioning exercises are most likely to drive positive RoI for the organisation. While doing our last Analytics Impact Index study, we realised that leadership and strategy has a far bigger impact on profit than technology and infrastructure in utilising data analytics effectively. In fact, investing in data and technology can have a negative impact without influence and buy-in of strategic leadership.

Now, some data: Only approximately 43 percent digital or analytics led programmes lead to improvements in top- or bottom-line. The remaining 57 percent invest in digital and analytics enablers, but unfortunately these don’t lead to any measurable, impactful business outcomes. Reason? Investment in analytics initiatives needs to drive business value. Ensure that your initiatives are aligned with your business goals and that technology assets and resources are optimally utilised across the enterprise. Do not get swayed into app enhancements or functional efficiencies.

Second, stay relevant. This is key in any data and analytics programme. And for that it is essential that the programme consistently understands and solves relevant customer issues. Surprisingly, this is often hard to achieve as data is the biggest pain point of most data and analytics programmes. In case of internal customers/ stakeholders your organisation, advanced analytical techniques such as Organisational Network Analysis (ONA) are helpful. ONA can graphically visualise how information and communication flow within the organisation by identifying the informal networks that lie within the organisation. Proactive identification of informal networks and key influencers and capturing relevant knowledge ahead of time can remove many not-so-visible roadblocks and unlock productivity improvements.

In case of external customers, ensure that you are addressing the latest customer pain points through customer labs. These labs work by incorporating multiple sources of input including CRM, call and text logs, market research and social media to uncover key customer concerns. What makes them so valuable is that they are exclusively focused on end-users and combine business, analytics and technology to continuously create innovative products and services (in partnership with stakeholders) to get the best results.

Finally, ensure your RoI metrics and prioritisation logic are on point. Coming back to strategic planning, many analytics transformation programmes fail to deliver results due to the lack of it in the initial phases. So a definite way to win is to ensure that you are developing a comprehensive and robust business case with the right set of KPIs for measuring RoI. Ensure stress testing and robust scenario planning is part of developing the business case to ensure that all possible risks and constraints have been built in. And key stakeholders are fully aligned on KPIs and desired ROI (and include even post-program KPIs).

Also ensure that your prioritisation logic includes multiple dimensions such as RoI, customer need, technology readiness, urgency etc. Initiatives that can be solved through traditional IT approaches should not be included as part of data and analytics transformations. These take up valuable money and employee resources, which ideally should be deployed elsewhere.

Analytics is not new for organisations. But the rise in the amount of data available and the extreme advancements in computing has lent an unsurpassable power to the analytics of today. And as organisations move toward more intense and elaborate data-driven strategies, quick access to analytical insights will continue to get increasingly critical in maintaining a competitive advantage across all levels of an organisation. And the mantra to win will lie in three simple truths: plan early, stay relevant and precise, and measure right.

The author is Director of A.T. Kearney.

The thoughts and opinions shared here are of the author.