High performance achieved through effective
organization
Cultivating an analytics culture is necessary to drive
transformative change, and deliver on the full potential of your analytics
investments. A prerequisite for high performance is being organizationally ready
to make faster, smarter decisions and to drive cross-departmental ownership for
the implementation of those decisions. While there are multiple facets involved
in organizational effectiveness, getting the right leaders in place, breaking
down silos, fostering the necessary culture and developing your talent are good
places to start.
According to a recent Accenture survey of 600
executives, eight out of 10 companies have not achieved their goals in
analytics. And only one out of 12 respondents expressed satisfaction with the
return on their investments.
Here is a simple example. At Harrah’s, now
Caesars Entertainment, service delivery metrics, such as the average time it
takes to greet a customer or to deliver a drink, are reported to management on
Sunday. The very next day, the property’s general manager can expect a call if
the revenues are down compared to the same week in the previous
year.
After an analysis of Best Buy’s loyalty program, data showed that 7
percent of customers were responsible for 43 percent of its sales; therefore,
Best Buy redesigned its store layout to meet the needs of those loyal customers.
Further, this giant retailer quantified the value of employee engagement to
customers’ in-store experience ― a 0.1 percent increase in engagement is worth
more than $100,000 in a store’s annual income ― to inform its investments in the
workforce.
Quick action is a distinguishing feature of examples such as
these. High performers do not simply gather and analyze data; they use the
resulting insights to make smarter decisions faster. Their leaders are in sync
on how to employ analytics in their service strategy and that vision percolates
down through the organization. As a result, middle managers measure the right
metrics, make decisions based on the best data available, and understand the
significance of immediate action on the basis of those decisions.
No
technological solution, simply layered on top of existing processes and culture,
can achieve these results. Further, existing analytical talent in organizations
rapidly grows frustrated with added complexity. To drive transformative change
fueled by analytics, employees should know how to use scenario-based or workflow
analysis tools and build momentum by overcoming organizational barriers. As
talent is hired and capabilities expand, pockets of analytical excellence
develop in companies.
Contrast that scenario to that of a high-performing
organization with a culture that understands and celebrates the capabilities
required to win with analytics. Due to the hard work required to build and
maintain such an analytics culture, succeeding in this endeavor raises the
stakes in the market. Accenture uses the term “organizational effectiveness” to
structure the multifaceted endeavors required to foster an analytics
culture.
One facet of organizational effectiveness, for example, is
promoting and reinforcing top leaders with analytical vision, passion, and the
ability to nurture leaders at all levels. Another is developing and organizing
talent with the right skill sets. The magic occurs when the interpersonal and
process strengths of an innovative, results-focused culture are combined with
the technical and data-mining skills required to deliver high
performance.
Fostering a High-Performing Analytics
Culture
Leadership, breaking down silos, and developing and keeping
talent — are fundamental to fostering a high-performing analytics culture.
1) Leadership
The single most important step you can take is to
promote leaders with a passion for data analysis at every level. Leaders in the
C-suite need to model appropriate behavior, but they do not own analytics in the
organization. Every manager and leader in the middle ranks has to take
responsibility for creating a more fact-based culture because through ownership
comes commitment.
It is also important for executives to take a hard,
honest look at how in touch they are with the existing culture before they
attempt to drive transformative change. In a recent Accenture survey, leaders in
400 organizations responded favorably to statements such as “This organization
places a high value on collecting objective data to improve the quality of
decision-making” and “In this organization, you get ahead based on merit and
objectively demonstrated performance rather than political behavior.” In all but
two of these 400 organizations, employees answered these questions in a very
different way from their leaders.
Having an accurate understanding of
their organization’s readiness allows senior leadership to assess gaps and
define a path forward to create an analytics culture. And this effort, in turn,
helps them to get in sync with each other regarding how analytics will be used
to support their strategic vision ― the value they want to gain. By translating
that consensus down through the middle ranks, leaders can confer ownership of
analytics to the appropriate people and thereby avoid what we call “the frozen
middle.”
Often an effective approach to achieving analytics goals is to
recognize how factors play together. As Tom Anderson, CEO of Integrity
Interactive, has said, “The beauty of analytics is that you find lots of things
that can be incrementally improved. If it’s a multi-plicate business, [like]
medical finance and you can improve each factor ― the number of doctors times
the number of patients times the percentage that seek financing ― by 10 percent,
it’s huge.”
Harrah’s took a similar approach by recognizing the role of a
number of service delivery factors for customer satisfaction. Tracking each of
these factors, such as the time required to greet a customer or deliver a drink,
allows them to be targeted separately if revenues slip.
2) Breaking down
silos
Silos naturally develop as organizations grow. Analytics in the
service of the enterprise, however, requires cross functional collaboration ―
what one UK-based healthcare company calls “boundary-less” collaboration. To
address this tension, organizations need processes to facilitate people working
together from all parts of the organization.
The products of
collaboration can then be applied in different parts of the organization.
Procter & Gamble is an example of an analytics high performer that has
established a central team to contribute to the bottom line in a variety of
disciplines. This team, called Global Analytics, tackles challenges such as
manufacturing site location, inventory management, supply chain design, and
strategic decision making.
Creating a single repeatable process for
integrating analytics into everyday work is a powerful way to counteract the
rigidity of “silo-think.” A closed loop decision making process such as that
shown in Figure 1 defines how data is leveraged to test hypotheses and support
decisions anywhere in the enterprise. Recent Accenture research shows that only
one in five companies currently has such a repeatable process in
place.
Breaking down silos also facilitates the collaboration required to
stay ahead of the competition. For example, as a strategic partner rather than
an order taker, IT can help business units access the quality data needed to
forecast more accurately, price more appropriately, and tailor offerings to
customers or citizens more effectively.
3) Developing and keeping
talent
A smattering of quants around an organization is not an analytics
culture. Up-skilling the workforce in analytic capabilities is quickly becoming
essential just to keep pace with market. While training workers in IT skills has
consumed the organization’s training departments in the past, the next 20 years
will be about integrating analytics into everyday work.
The bar is also
rising for new hires. One financial services company, for example, requires all
potential employees, including senior executives, to take a series of tests to
determine analytical and financial aptitude. One successful hire joked that he
might have been “the only HR guy who could pass their math test.” Analyzing the
talent in the organization is as important as hiring talent with a passion for
analytics. This application of analytics can provide a clear advantage to
companies that use customer satisfaction as their
differentiator.
Harrah’s, for example, analyzes the effects of its health
and wellness programs on employee engagement. In this way, the company showed
that a rise in preventative care visits to its on-site clinics resulted in an
annual decrease (by millions of dollars) in urgent-care costs.
One reason
Harrah’s chose to capture wellness metrics is because its leadership team
understands that happy, healthy employees provide better customer service.
Gathering this data provides insights on revenue growth as well as on health
insurance and sick days. It is an example of the value of selecting the right
metrics, however seemingly unrelated, to help make decisions that support the
corporate strategy.
Another use of talent analytics is to retain
high-performing employees. Google has placed sufficient strategic importance on
talent retention so that its people analytics function has a staff of 30
researchers, analysts, and consultants. As Laszlo Bock, Google’s vice president
of people operations, says, “It’s not the company-provided lunch that keeps
people here. Googlers tell us that there are three reasons they stay: the
mission, the quality of the people, and the chance to build the skill sets of a
better leader or entrepreneur. And all our analytics are built around these
reasons.”
This article was provided by Accenture.
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