In an age where the technology playing field and access to data is becoming flatter, the question around where do organisations find competitive advantage is becoming a C-suite issue.
Based on a survey of 2,719 respondents across the globe and interviews with 28 executives, MIT Sloan Review and SAS found that organisations achieving the greatest benefits from analytics are also much more likely to have a clear idea on how they recruit, develop and deploy key talent within their organisation.
The scaling challenge
8% of company leaders report in engaging in practices identified as key enablers for analytics at scale
Key to success in this challenge, will be the need for circa ~4 million business translators to play the role of connecting data science talent to business questions. Getting this final mile right will mean the difference for Chief Analytics Officers and building an effective data culture. Translators are not Data Scientists. Instead, translators play a critical role in bridging the technical expertise of data scientists with the operational expertise of business frontline managers.
By 2026, the McKinsey Global Institute estimates that demand for translators in the United States alone may reach two to four million.
We have found some key skills of translators that have been successful in contributing to analytics transformation:
Putting business value front and center
Connecting business value. Often, managers and leaders do not have the head space or time to take on advanced algorithms — as interesting as they may be! The ability of translators to structure the conversation around what the business is trying to achieve — where are we going, and what you’re trying to understand through the lens of our customers is a critical baseline skill. Too often, teams get caught up by starting with the data. Translators enable them to start with the business value they wish to create and apply analytics from there.
Great translators possess strong facilitation skills to be effective here.
Cross functional agile mindset
Establish a common language. Starting with senior leaders, organisations need to establish a consistent and simple way of talking about data across business units. This consistent and simple nomenclature will allow translators, to jump from data project to business conversations and get up to speed quickly with the business need. A consistent language around what is a priority, enduring, or essential data requirement will enable the team to get on the same page. .
Great translators possess effective agile project management skills.
Exploit and re-use analytics
The average utilization of analytics models is <20%
In time, through embedded ways of working and rituals, your translators will start to join the insights around your organisation to what data is being used to boost business performance. As the bearers of business insight, your translators will be able to build communities of best practice that will in time start to crack data silos — the early stages of building a data ecosystem. This requires strong reinforcement from senior leadership at the start, and a commitment to organisation wide diffusion of insights.
Great translators build communities.
Maintain an enthusiasm to Share!
We get asked frequently how you balance embedding analytic talent deep into the front line of organisations whilst aligning to the centre. The answer is not an either/or but a dynamic tension that needs to be well managed. The critical shift here is from a centre of excellence approach to an effective data culture. Whether your translators are working on specific projects or clustered by business function, they play a critical role in sharing success across the business. Move beyond a static data warehouse or lake mindset (as critically important as these assets may be) and towards a Data Cafe way of thinking, where data success in one part of the organisation can be shared and used to another effect somewhere else.
Great translators effectively manage business leaders.
Industrialise an operating framework
This is about culture. Here is a framework we use for translators to use in their teams everyday:
- Align to what’s important to the business. Work with business unit leaders to prioritize efforts.
- Data — Ask better questions to data. Work with the business to identify gaps in their understanding to produce the most meaningful results.
- Analysis — Allocate analytics to the most meaningful issues. Work with the business to ensure that the analytics solution is clear for business users.
- Pivot — Ensure decision follow through. Work with the business to articulate recommendations and that the business can execute on.
- Translate — Share and break silo’s. Work with the business to translate insight among other business users.
Conclusion
30% CAO annual turnover in North America. 2–3 years average tenure of a CAO
If you are an Analytics leader, business translators will benefit a data culture hugely as we move into the analytics-driven era, providing that they are deployed carefully and the business teams are ready to receive them with the right social operating mechanisms. Organisations that get this final mile right, will start to use data to fuel growth across all areas of the business against the most important issues and build an effective data culture.
If you’d like to understand how you can build a data culture inside your organisation, contact us at see6.
