As outlined in Developing an Analytics Strategy: The Role of Culture, there are five facets to “cultural infrastructure” that organizations must address to realize the full potential of analytics. This may require significant cultural change, which must begin with executive leadership, i.e. setting the “tone at the top”. We recommend appointing an Analytics Champion to maximize value from analytics. Here, I’ll describe the key traits of an Analytics Champion and how they can set up an organization for future “wins” with analytics.
Key Traits for an Analytics Champion
The analytics champion must be an advocate and a change agent who disseminates the analytics strategy and fosters an analytics culture where everyone is comfortable using data-based insights to improve the quality and effectiveness of their decisions. Five traits to look for in a champion are:
- Credibility: Trusted and well-respected because of a proven track record of managing “difficult” projects to successful completion.
- Empathy: Listens to, and addresses, fears and resistance to change as new steps are taken on this unfamiliar path.
- Problem Solver: Willing to roll up their sleeves and work to overcome technical and cultural challenges that arise through each stage of implementation.
- Commitment: Embraces the analytics strategy and promotes a consistent interpretation of the goals for analytics.
- Flexibility: Data-driven decisions require ongoing evaluation of their effectiveness. A champion must recognize when a facet of the analytics strategy is not working and work with all parties to redefine a solution.
To be effective, it is essential for the Analytics Champion to have the full support of the executive team and to be armed with a well-formed analytics strategy. Our Executive Analytics Strategy session is designed to help executive teams create, or refine, an effective analytics strategy to improve organizational decision-making, provide recommendations on how to grow analytics capabilities, and plan potential projects that will provide early momentum and return on investment.
The Analytics Champion’s Role
The Analytics Champion is entrusted by executive management to refine and promote the organization’s analytics strategy and measure the impact the analytics program has on key stakeholders or decision makers. To accomplish this, the champion will need to address the following items:
Promote “data as a strategic asset”
Remind all stakeholders of the relationship: data + use = value. This motto, from USASpending.gov, proposes that data assets only have value when they are used to achieve a goal or answer a question. The analytics program is mechanism by which to unlock this value, and the fastest way to demonstrate this is to complete “quick win” projects.
Address resistance
Resistance to change can arise from any level of the organization, as outlined in the next section. An effective champion must listen to, and address, concerns without sacrificing the overall goal.
Promote collaboration
As technical infrastructure improves physical data sharing, the analytics champion must work to also reduce any lingering cultural or regulatory barriers that prevent business units from sharing data with a centralized analytics team. For example, if personally identifiable information (PII) prevents the analytics team from using employee data to create an analytics product for the HR department, the analytics champion can work with all parties to implement a data de-identification solution to allow the project to move forward.
Promote a culture of evaluation and improvement
Units must regularly evaluate their effectiveness to keep pace with a continuously evolving business environment. The analytics champion must demonstrate how analytics can improve the organization’s ability to accomplish its mission, streamline workflows, and provide significant return on investment. Even if some insights are unwelcome or inconvenient, the analytics champion should reward stakeholders for trying new approaches when suggested by the data.
Educate and empower the workforce
Having access to data-based insights empowers all levels of the organization to make informed decisions. The analytics champion must promote effective data governance, security, and privacy so that stakeholders understand how to access and use data within an acceptable framework.
While all the items in this list are interrelated, the top two are often the most challenging and most important tasks for the analytics champion. Let’s perform a deeper dive into these two tasks.
Promote Data as a Strategic Asset
Organizations often fail to treat data as a strategic asset that improves decision-making throughout the organization. Because of limited infrastructure, it could be the case that previous analytics initiatives required significant effort to compile and prepare the data for analysis. Those involved may have felt the reward was not worth the effort. In the most extreme cases, messing with data may be viewed as “something extra to do” that keeps people from doing their core work.
An analytics champion must recognize the usual cultural starting point, or baseline, of the organization: Data is viewed as a monetary or resource expense, not as a strategic asset. To address this, first recall that accounting defines an asset as a “resource owned by a company which has a future economic value.” Let’s break this down:
- Assets do not necessarily have intrinsic value, but rather have “future” value that must be realized through use.
- Assets are associated with liabilities incurred by the asset owner. In the case of data assets, this includes the analytics program cost (data scientists, analysts, software, etc.) as well as the earlier cost to acquire, store, maintain, and secure the data.
An astute analytics champion will recognize that these costs represent the investment needed to unlock the future value of data assets. The champion must help decision makers find ways data can provide value to them and their work. Otherwise, the data will not be used, will not show value, and will continue to be considered a cost without the benefit associated with an asset.
One technique to accomplish this is to use “quick win” projects: Work closely with stakeholders to find “pain points” (i.e. problems leading to inefficiencies or other annoyances) that data + analysis could suggest ways to address. Once candidate projects are identified and prioritized based on their likelihood of providing a quick win, the analytics champion must advocate for the resources and win over the skeptics long enough to see the project through to completion. This requires addressing multiple forms of resistance.
Address Resistance
The Analytics Champion must have a multi-faceted approach to win over different organizational levels:
C-Level resistance
Preparing the technical infrastructure for an effective analytics program may require significant resource investment for an unknown return. This should be addressed in two ways. First, where possible, start with a small project requiring minimal infrastructure to secure a quick win with positive expected ROI. If this is not possible, then show examples where others in the same industry have benefitted. Second, separate the liabilities associated with data assets into two components: maintenance and usage. Assuming the organization is already maintaining data, then the cost of an analytics program falls purely in the usage category, making the cost to unlock value incremental. This provides a more accurate determination for ROI.
Department-level resistance
Process owners may resist the perceived effort associated with data governance processes needed to make “data hygiene” sufficient to support analytics. The analytics champion must find ways to show how such efforts will result in recurring, long-term benefits to the organization that will, in turn, reap tangible rewards and recognition for the department. Again, quick win projects can help. However, the analytics champion should not stop there: important tasks are best accomplished with a dependable ally with shared interests. The champion should engage the organization’s information security group—they not only understand the benefits of data governance, but have experience mapping those needs to regulations and/or articulating the reputational risks of not embracing data governance. Such an alliance can create synergies for targeted investments that address multiple organizational needs.
Front-line worker resistance
As with business process owners, front-line workers are not interested in extra work if it is not reflected in the metrics used to assess their performance. An astute champion addresses their question: “What’s in it for me?” Integrating analytics solutions into existing workflows reduces incremental effort and empowers front-line workers to make more informed decisions and improve job performance.
Summary
At the most strategic level, analytics allows organizations unlock latent value from their data to gain insights, accomplish business objectives, and improve profits. While these insights should empower everyone in the organization, many organizations resist the cultural changes needed to benefit from an analytics program. As a first step, executive leadership must establish and support the analytics strategy. Then, designate an Analytics Champion to engage stakeholders to unify that vision, understand and address pain points, overcome resistance to adoption, and demonstrate the value from analytics though “quick win” projects . Doing the work necessary to pave a good runway will ensure analytical results have a safe place to land. Put simply, the Analytics Champion advocates the vision for analytics and lays the groundwork needed to foster ongoing success of an analytics program.
