CDAO México 2018

It was a pleasure to witness the many insightful keynote presentations by renowned brands such as: Legendary Entertainment, The Kellogg Company, Reddit, Capital One, Stanley Black and Decker and many more…

The paradigm has certainly shifted from a strategic to a more tactical imperative. There was a great emphasis on producing a value-driven approach to developing analytics capabilities at scale. Case studies dominated the agenda; providing detailed analysis from executives on how to create business value from your data assets.

“Although value was at the core of the discussion, many firms still struggle with developing a means to measure ROI attributed to analytics initiatives, with 80% of our attendees stating that analytics ROI was not measured in 2016.”

This is a staggering statistic, and one of the many impactful truths which pervaded the event. Here are my top takeaways from the conference:

The Great Dilemma – Product vs Project vs Capability 

Although not one of these approaches will provide a universal solution, organisation’s must be clear on which avenue they’d like to take when employing enterprise analytics. Many speakers discussed the notion of analytics as a product/service, and the importance in marketing that product/service to maximise buy-in and adoption. However, analytics executives may look to take a capability-based approach, but one cannot simply build an arsenal of analytics capabilities without a clearly defined purpose and value generated for the business. Project-based analytics may have its perks as it pertains to adoption. It’s also more likely to have clearly defined benefits, however, organisation’s that take this approach must be weary of the scalability of such endeavours. Project-based analytics can prove to be rather niche, thus requiring a heavier commitment in terms of labour. Many of today’s organisation’s are now opting for a hub and spoke structure which combines a centralised team with distributed smaller teams embedded into the business functions themselves. This provides the benefit of both rolling out standardised analytics practices but also benefiting from the knowledge ingrained in each respective business unit.

Measuring the value of Analytics

As mentioned in the opening of this article, 80% of our attendees stated that analytics ROI was not measured in 2016, and 71% of attendees stated that their organisations view analytics as a cost-centre. It’s worth nothing that these statistics are remarkably similar. It would not be completely outrageous to conclude that perhaps the reason why analytics is viewed as such, is partly due to the lack of measurable ROI. Analytics initiatives cannot expect to receive further investment if value isn’t measured and communicated. Jose Murillo, Chief Analytics Officer at Banorte consolidated this fact in his presentation titled, “Getting a seat at the table”. He spoke of the importance in communicating results to key stakeholders especially the C-Suite and celebrating the achievements with those involved. This communication of wins can be an incredibly powerful tool in effecting change and nurturing your organisation to see the benefit of analytics.

Functional competition is a real challenge!

Prioritisation at both a strategic and operational level can often mean the difference between success and failure. This remains true for many organisation’s in attendance at CAO Fall who spoke about the difficulties with prioritisation and meeting the needs of business functions. As departments compete for the limited time/resources of analytics teams questions which projects align with the overall strategy and which projects will create the most value for the business.

Enter the Data Translator

The talent conversation has evolved and become more critical now more than ever. As technology and analytical tools become cheaper and more readily available, the competitive advantage will ultimately lie in the data being analysed as well as the creative solutions put forth by the teams themselves. Rather than searching for the illusive “Unicorn”, organisation’s looking to obtain analytics success are investing in teams with diverse skill-sets. Effective communication coupled with a deep analytical understanding came out on top as attributes heavily desired by CAOs and analytics leaders. Which opens up more questions, where will these individuals come from? Internally? What is academia doing to help prepare students for these needs?

AI & Machine Learning are here to stay

AI is becoming much more than just a buzzword, with 56% of attendees investing in AI. Rather than focusing on a theoretical strategic imperative, practical case studies from Stanley Black and Decker, Honeywell, Reddit, John Hancock spoke of the triumphs in leveraging AI and Machine Learning within their respective fields. Themes of consumer personalisation, organisational agility, revenue creation were in abundance and truly cemented AI and Machine Learning as valuable commodities in the present and future quest for analytics excellence.

If you would like to review the presentations from Chief Analytics Officer, Fall you can subscribe to our Chief Analytics Officer Hangouts for free access to C-Suite inspired and created digital resources focusing on the rise of the Chief Analytics Officer role, impact on Big Data & Analytics Strategy and the technology landscape driving innovation (amongst others).

If you’d like to learn more about these themes and understand how the conversation is evolving, join us at the Chief Data & Analytics Officer, Mexico conference taking place on January 30-31 in Mexico City. Browse the registration options and secure your place here.