The insights-driven leader: boosting leadership skills with hard facts
Do you know the situation when one of your most valued employees quits unexpectedly and you did not see that coming? That is just one example in which an insights-driven leader would have been prepared.
Today, leadership should no longer be based on instincts or be driven by circumstances. Instead, an insights-driven leader uses analytics to derive insights to prepare and make decisions. This does not mean leaders will become cold-hearted robots lacking human sympathy. Rather, leaders will still use their soft skills and combine them with insights enabling decision-making and leadership to become more objective, transparent and effective.
Before going into the details of insights-driven leadership, let’s have a look at the primary roles of a leader. Usually, a leader is someone who…
- …can be found in all business units of a company as a team and/or functional lead,
- …works on strategic & financial issues,
- …manages and guides teams,
- …bears functional and people decision-making responsibilities.
Today, these primary responsibilities occur in an environment which is changing faster than ever. Market conditions, employee demands and demographic change are just a few examples on the challenges that leaders need to tackle.
Beyond these primary responsibilities leaders are also confronted with underlying challenges that arise from what is known as a “VUCA-environment.” Volatility, Uncertainty, Complexity and Ambiguity are key aspects of today’s changing business environment. Thus, to keep pace and a clear head for decision-making, the leader needs strong soft skills and decision-making backed-up with data insights.
Hence, an insights-driven leader needs to put emphasis on two dimensions: Data capabilities and data management.
Data Capabilities
Data capabilities define the maturity of your technological set-up within your company. Divided into infrastructure, handling and modelling it describes three maturity grades along the data journey. The most important factor is to have tools available to handle volume, velocity, and variety of today’s data. Business and IT departments will need to work hard and closely together to integrate all relevant internal and external sources of data to build up the base for insights-driven decision making.
Data Infrastructure
Regardless of the scope of data usage or the characteristic of the data (quantitative or qualitative) a good data infrastructure including accurate data collection is essential to maintain the integrity of your analytics. Also, a formal data collection process is necessary to ensure that the data collected is defined and accurate, so that subsequent decisions and insights based on the data analytics are correct and valid. This includes developing policies and procedures on how to deal with important data. In particular, addressing concerns about the confidentiality, security and retention of data to ensure that recorded data is not altered, deleted, lost, or accessed by unauthorized users.
Data Handling
When a good infrastructure is set up data handling deals with getting aware of your relevant data. To convert data into information it is essential that the right data is used and that the right data is extracted and separated carefully from others. The result of that data search exercise is a clearly defined data set (data model) along your relevant analytics use cases.
Data Modeling
In the final step, data modelling enables you to describe and predict different use cases with the help of data. In general, we can define between statistic modelling, predictive modelling and prescriptive modeling — the final phase is prescriptive analytics which goes further than only predicting future facts by also suggesting concrete actions and explains why something will happen. To enable prescriptive analytics, it is important to combine different disciplines such as signal processing, applied statistics, machine learning etc. Ultimately, a leader will grasp opportunities and decrease the involved risks by applying these advanced analytics.
Data Mindset
The dimension data mindset is about making the organization and the employees ready to use and benefit from data analytics. Establishing a data mindset therefore means ensuring organizational readiness, implementing a data culture and drive the education for data and analytics.
Organizational readiness
In order to leverage data analytics in the day-to-day business, data must become ubiquitous to everyone in the organization. An insights-driven leader will start to orchestrate relevant business data. Roles and processes within the organization must be aligned accordingly, making sure to close the gaps to become an insights-driven organization. This includes exemplary measures such as appointing a Chief Data Officer (CDO).
Data culture
Establishing a culture that lives the opportunities and responsibilities is mostly about awareness and acceptance of data including all aspects, from collecting to analyzing data to generating insights. To establish a sharing culture is essentially important. Being open to share and distribute data is key but should be handled with care.
Data education
In order to establish a data culture understanding the opportunities and responsibilities that come with it need to be part of a structured education roadmap for the whole organization. In terms of capabilities, education means enabling employees for the skill of interpreting data and insights which are the results of complex analytics. In this context, data visualization skills are a complementary key skill to make analytics possible within your organization.
An insights-driven leadership-matrix
Putting emphasis on those two dimensions above, will step by step grow your capabilities as an insights- driven leader. Below, our insights-driven leadership-matrix helps you to find out your current maturity level. This matrix is part of our analysis tool to identify the starting point and priorities for leaders on their journey towards an insights-driven leader.
Beginners are about to start their journey to become insights-driven, but first they need to update their IT landscape and start by educating their workforce.
Believers understand the crucial role of data analytics and even prepare their organization and educate employees to use them and understand the need to build data capabilities.
Techies create an IT and data management landscape but have not prepared their organization for working with data analytics and levering insights.
Insights-driven leaders advance their leadership by combining their soft skills with insights. They have advanced data analytics capabilities supported by a data-driven mindset and an organization ready to act on insights.
In the future, data-based decisions will become the new standard on how to guide a company. Ultimately, the leaders of today will face a fateful decision: boosting your leadership through data insights or losing relevance over artificial intelligence.
If you now see the need to become a more insights-driven leader and want to know more about your journey to get there? Feel free to contact our experts from Capgemini’s Insights-Driven Leadership practice.
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About the authors:
Joana Koester and Denis Tintman are management consultants at Capgemini Invent in the Insights Driven Enterprise Team. They accompany global clients in digital transformation and insights-driven innovation with a special focus on data analytics and leadership.
PS: Want to get in touch? Check out the profile from Joana and Denis on LinkedIn.
