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Operationalizing analytics with global business services
Business analytics and service delivery transformation
For many, business analytics is being embraced as a way to transform service delivery.
While creating analytic insights can be a feat on its own, there are often hidden barriers that make taking the next step—achieving real business benefits—more of a challenge. For some, using global business services (GBS) is a way to both produce, and more importantly, achieve acceptance of actions critical to successful analytics programs.
Mastering the data analytics machine
Building a better machine
GBS can develop a “factory” approach to insight delivery by focusing on a common, consistent approach to producing data-driven insights—define the processes, develop the tools, and provide quality assurance oversight and continuous improvement.
Focus on speed and efficiency
Effective analytics require speed. If production is delaying the delivery of insights to the business leaders who need them—that’s a problem. It is important to define the level of precision needed based on the risk/reward of decisions being made. There is a difference between the level of analytic rigor needed to assess a budget variance on a monthly basis and a market assessment for a new product launch. Sometimes “good enough” is good enough. The tradeoff between speed and accuracy should be defined based on business needs, not mathematical precision.
Users first, users last
Many tend to focus on the technology aspects of business analytics, since it’s the technology that is making analytics possible. While technology is necessary, it is never enough on its own to get the value analytics offer. User experience is a critical consideration as you define how to produce and present insights. While reams of data may excite some, it can overwhelm others. Similarly, while some prefer graphical representations, others need the narrative to feel confident in the outcomes. Too often we have seen this last mile of analytics ignored, which can impair analytics programs.
Find and address hidden barriers
Plan for the personal impact
Presented with a blinding new insight from analytics, the response is often not to celebrate, but to defend. For many leaders, accepting the finding may be viewed as taking responsibility for a negative result. After all, analytics provide deeper insights that can uncover waste or identify savings opportunities. Identifying these weaknesses may lead people to fear that they will be held responsible for the result or perhaps required to fix something they didn’t know was broken. It would be naïve not to expect bad news to be rejected or challenged. If the culture isn’t rooted in improvement and agility, then introducing an analytics capability may drive less innovation, not more.
One option is to manage the dissemination of analytics through a GBS structure. By embedding analytics under a continuous improvement team, analytic insights are part of a collaborative group, and individuals who have the most to lose and could be viewed as part of the problem now have a role as part of the solution. This simple act can help remove the sense of personal exposure and drive a focus on making changes that matter, rather than assigning blame.
Organizational obstacles await. Prepare accordingly.
Another barrier lies at the organization level. In many cases, functions or business units may want to make a change without realizing the upstream or downstream impacts of the proposed changes. Analytics may identify a bottleneck in a process such as a delay in sales contracting caused by slow response time from legal or risk review. While the analysis makes identification easy, the remedy could be much more difficult to implement. In this case, legal may rely on outside counsel to address parts of the review, or they may be understaffed. From a pure numbers standpoint, the problem and solution are in the same function. Unless legal agrees to work harder and longer, fixing the problem isn’t easy. One alternative is to work with a GBS continuous improvement team, which may identify the root cause as being the sheer number of non-standard contracts used by sales. The contract burden may be reduced by having pre-authorized contract templates to reduce the demands on legal and allow them to focus on fewer exceptions. Here, the idea is to move beyond merely identifying problems to focusing on solutions
Find a way to fund good ideas
Even when virtually everyone agrees on the right course of action, any change is likely to impact financial results, positively or negatively. In too many cases, the greater good runs smack into budget realities. Once an initiative is developed and accepted, it can still be deferred simply because the costs borne by one function to save money in another weren’t in the current budget. This can be avoided by having a GBS team responsible for making the changes and funding the unbudgeted costs.
Change the organization
Understand the old guard
Historically, experience mattered in decision making: People were promoted based on their personal experience and knowledge accumulated over time. More senior, experienced managers trained younger, less experienced staff who over time got promoted. Decisions and strategies were developed at the top of the pyramid and executed at the bottom. But today, that’s changing.
Embrace the new order
Data-driven insights are often produced at the lower level by less experienced team members. While they are still reviewed and validated at the top by the leadership level, experience isn’t as valuable as it once was. In effect the top-down becomes bottom-up, flipping the power structure on its head.
Experience is needed to provide the guardrails that data lacks on its own to prevent an organization from making poor decisions based on available information, while ignoring experience and the realities of the marketplace. Evolving an organization to produce analytical insights, creating a supporting environment to act on it and recognizing the value of experience in honing solutions may be the best way to achieve the benefits of analytics.