Rebooting analytics
leadership: Time to
move beyond the math
PART
II
2. Building an enterprise capability
Catalysts also play the
leadership role in analytics capability building across the organization,
including working closely with the following:
·
The
business on talent
strategy—from hiring analytics translators to implementing agile
software-development processes. One analytics leader we spoke with used
internal hackathons that teamed analytics staff with business units to solve a
critical problem. This not only helped analytics staff build translator skills
to bridge data science and business but also helped raise the business’s
analytics IQ and gain a new cadre of “believers.”
·
IT on data and technology
strategy, including data governance and analytics methods and tools.
·
Risk
and compliance (including the
chief risk officer) as well as leaders across the organization on
risk-mitigation strategies.
3. Integrating advanced analytics into the
workflow
Catalysts lead and
advise on how to integrate advanced analytics insights into workflows and
decision making. They help business leaders understand that an analytics-driven
organization requires a different approach to managing and how teams work. They
know the business and its objectives and can pinpoint opportunities to embed
more sophisticated analytics.
For example, the
insurance analytics leader we spoke with drew from design-thinking methods to help his business
identify how and where new data sources, such as genomic data, might influence
traditional underwriting workflows.
Another analytics
leader worked closely with his counterparts to educate and prepare the
organization to overcome the human biases that could sabotage the move from
traditional manual processes to AI-augmented processes.
4. Acting as a change agent
At their core,
Catalysts are change agents—able to navigate organizational barriers to
analytics adoption. Here, communication and relationship building on both
individual and organizational levels are necessary. Leaders we spoke with used
town halls, one-on-ones, and monthly and quarterly update meetings with key
stakeholders to build support.
One leader we spoke
with used a tiered approach—first building support with the top ten influencers,
then another 50 key influencers, then 500, and beyond. Change doesn’t occur
overnight, and this work can take years. He said, “Ultimately, the goal is to
get to the point where every employee has an analytics mind-set.”
5. Advising their boards and CEOs
Catalysts support and
advise their boards and CEOs, providing them with a foundational knowledge on
the role of AI, orienting members on the company’s journey compared with
competitors, and educating them on the governance issues the company will face.
They present both the fullness of the opportunity and the difficulty of the
journey through one-on-one meetings and other venues. For example, one leader
we spoke with identified data scientists and other team members who delivered
“outsized contributions” and scheduled informational conversations with the CEO
so they could share the work they were doing. “It was a great way for the CEO
to gain a deep understanding on some of the key challenges, opportunities, and
wins that we’d had and a great way for the data scientists and their managers
to receive recognition from the CEO,” he said.
Exhibit 3 PLEASE SEE THE ORIGINAL ARTICLE
How to become a Catalyst
Any CAO not regularly
engaging in these activities is likely not yet a full-bore Catalyst. A sure
sign that a CAO might be more on the path to “cataclysmic” rather than
“catalystic” is that he or she is still “pushing” business units to embed
analytics in meaningful ways rather than experiencing a “pull” from business
units to partner strategically to transform the business.
“In the beginning, you
have to do what the business units are asking for—like producing a report on
customer attrition,” said one analytics leader. “Over time, we saw the nature
of the requests began to change. Instead of asking for a report, business
leaders asked us what actions we could take to drive change.”
Based on our experience
with helping CAOs make the switch to Catalyst, there are three ways to get
started.
Take time to take stock
It’s important to take
the time to conduct a thorough assessment of where the organization stands in
terms of analytics IQ and adoption as well as where you stand as a leader.
To assess the current
organizational situation, answer questions such as: How much value have prior
analytics initiatives delivered? How much credibility does the function
currently have? What expectations exist when it comes to both investment in
analytics and business impact? Where are the pockets of resistance and
openness? What tone did my predecessor set? How did he or she lead?
Understanding both past
and present organizational dynamics will help illuminate existing perceptions
that might derail your progress.
At the same time, it’s
important to take an honest look at your own leadership skills. All leaders we
interviewed highlighted that their ability to influence every level of the
organization was critical to their success. “Most of the day-to-day leadership
is happening in small-group settings where you’re influencing folks in their
thinking,” said one leader.
How you’re perceived
will have a strong influence on your organization’s success. Are you balancing
expertise with empathy? Do you actively encourage participation and input from
others? Do you bring a positive attitude regardless of how things turn out?
With this body of
self-knowledge and organizational knowledge, you can better plan your strategy.
One CAO we recently worked with realized that while he excelled when it came to
the more technical aspects of the job, breaking down silos and getting control
of the narrative didn’t come naturally to him. To succeed, he not only hired
new talent who could complement his leadership but also enlisted the help of an
executive coach for six months to help him manage the difficult conversations
he had to have as he worked to forward the analytics agenda. Coaching offered
the leader proven approaches so that, regardless of the outcome, participants
left the room with greater understanding and respect.
Create a stakeholder map
While determining the
state of the union offers an organizational perspective on barriers to change
(including yourself), the stakeholder map can help identify key decision makers
and gauge their individual appetite for analytics.
This is vital
reconnaissance for everything from building your communication plan to
prioritizing which analytic initiatives to pursue and when. The
financial-services leader we spoke with used his stakeholder map (literally
drawn as a pyramid on a piece of paper) as a compass to guide his
relationship-building journey with nearly 60 general managers and
organizational leaders across his company. He began his efforts focused on 15
leaders he deemed most critical and, over his first weeks and months, scheduled
regular meetings to learn their priorities, concerns, and expectations directly.
“Everyone comes from a different place, and there’s a lot of difficult
conversations that need to happen,” he said. “Making personal time can help.”
Increase your communications, regardless of
where you are in the analytics transformation
The one regret we heard
from successful analytics leaders was that they spent the bulk of their time at
the outset on talent development and getting the technical details right. In
hindsight, they told us, they wished they had spent more time on communications
and alignment with the business in their early days to pave a faster path to
success. The analytics leader of an online retailer found that external
brand-building activities, such as externally published articles about the
company’s analytics innovation efforts, not only supported talent acquisition
but also drove increased internal support. “Inevitably, people would receive
the published article from friends and colleagues at another company,” he said.
“When someone in operations gets a note about how exciting the work is that the
data-science team is doing, you get a lot of credibility.”
Ongoing communications
also help build the bridges necessary for change. Being a change agent isn’t
easy—as is commonly said, it can be lonely at the top—and many times it puts
leaders at odds with others throughout their organizations. One CEO advised his
analytics leader that “things may go your way only 50 percent of the time, and
the other half we’ll do something that’s not fully aligned with where we want
to be because the short-term benefit is greater to us.”
Those who are
successful typically find that a collaborative, problem-solving style fostered
through ongoing communication is imperative.
Ultimately, we believe
the Catalyst will become the dominant persona for CAOs of the next decade. The
Catalyst skill set best positions CAOs to not only overcome today’s challenges
but also tackle those their organizations could encounter in the future—some as
a result of the Catalyst’s own success. For example, with their experience to
date in capability building and deep knowledge of analytics outputs, Catalysts
are well positioned to help in reskilling efforts for those whose jobs become
more automated as AI and other advanced analytics become business staples.
CAOs who embrace the
Catalyst persona may also be better prepared to accept wider leadership
opportunities. Traditionally, CEOs have been hired primarily based on
leadership and industry experience. But as data and analytics become more
ingrained within businesses, we expect that the next wave of CEOs will also
need strong analytics expertise. With analytics acumen and Catalyst leadership
skills, today’s CAOs could well become tomorrow’s CEOs.
By Brian McCarthy, Chris
McShea, and Marcus
Roth
https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/rebooting-analytics-leadership-time-to-move-beyond-the-math?cid=other-eml-alt-mip-mck-oth-1811&hlkid=f5c82c5620034dbeb6216c7ac7e7d1fd&hctky=1627601&hdpid=b3b5de99-d83f-4794-8650-4068aa0b1084
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