A leadership team is discussing the recent performance of its business and is attempting to develop action plans to move the organization forward. Several members of the leadership team vent frustration at the lack of information coming from the data available within the organization – an issue that persists despite building dashboards, investing in a “Business Intelligence” platform, and hiring team members to focus on data and analytics. Exclamations of, “This has to exist!” and frustrated sighs of, “What good is an analytics team that does not produce good analytics?” can be heard throughout the meeting.
The above scenario is not uncommon, and the frustration, questions, and confusion are often warranted. At SLKone, we are frequently approached by our clients with exacerbated requests for guidance on how to build a better analytical function. So, why does this happen, and how can we help?
Common Characteristics and Shortcomings
In our experience, there are four common characteristics associated with an ineffective or underperforming analytics function. First, data integrity and governance are in question across the organization. Second, data is unable to be translated into information. Third, information is presented ineffectively. Last, management tends to mistrust information that contradicts their predispositions. Often, these characteristics are happening concurrently, but this is not a requirement. Let’s dive in and explore each of these in more detail.
Poor Data Integrity and Governance
The first – and most prevalent – shortcoming is poor data integrity and governance. Today, data is generated and continuously captured from many sources, including our cell phones, tablets, ERP systems, email, and many others. With the vast amounts of data available and terms like “big data” floating around, how do organizations still generate ineffective analysis that lacks insight? The answer is simple: the adage of garbage-in-garbage-out is the law of data and analytics.
Most organizations task their IT function with maintaining data integrity and governance; however, most IT functions do not control the inputs to the systems. The IT function becomes a reactionary component that seeks to mitigate the damage of its data rather than a proactive part that supports better analytics. Business operators often control data inputs and, when they are not well aligned with the goals of data governance compliance, the data entered becomes suspect.
To facilitate data analytics and insights, data integrity and governance must be addressed as a fundamental tenet. It is an initiative that must start from the top and be passed to all members of an organization as it requires continual monitoring, updates, and adherence across the enterprise.
The Data-to-Information Gap
The second shortcoming we recognize in this challenge is what we refer to as the data-to-information gap. By definition, data are individual facts or statistics, and information is the knowledge and insights derived from data. The data-to-information gap is the space between data points and insights.
Unfortunately, it takes more than connecting or correlating points of data to bridge the gap. A combination of business savvy and technical knowledge must be used to coherently connect the right pieces of data to derive accurate and useful information. Further, it requires critical thinking, industry insight, the identification of deviations from trends or norms, as well as intellectual curiosity. Should this capacity be lacking in an organization, the data-to-information gap may never be closed.
Leadership must view this organizational need as an imperative and bring or develop the right skill set within the business. As this skill set is established, leaders must align on the business drivers and need for information in addition to bridging the IT and analytics functions. This is often the role of the Financial Planning and Analysis (FP&A) function.
Presentation of Information
The third – and most visible – shortcoming is the presentation of information. Arguably the most important job of the data analytics function is to present the information in a clear, impactful, and actionable manner. Clean data and insightful information are worthless if they are not presented in a digestible manner. Too often, our clients show us dashboards of key performance indicators that do not provide value to their organizations. These dashboards are often created in silos and do not take into consideration the real business needs of the final user.
Creating dashboards and presenting information is a team effort that extends beyond the data analytics and FP&A function. It is imperative to include all stakeholders and understand the goals and objectives that business managers are seeking to achieve. Then, and only then, can dashboards be developed to deliver clear, impactful, and actionable insights to business managers. The insights and presentation of the data must be replicable to add value. Alignment around the information to measure will direct the “what,” but the “how” must also be addressed.
Organizations should carefully consider the mechanism with which to present information. There are several system platforms which exist for dynamic displaying of information, but a new system is not always required. Ultimately, any method of presentation will need to be refreshed, maintained, and adapted as the business evolves. This is a critical component of enabling the presentation of information.
Acceptance of Information
The final shortcoming is often the most difficult to overcome. It occurs when the data is clean, the information is insightful, and the presentation is impactful; but the recipients of the information do not buy-in. In most cases, we find managers develop a narrative around their business. They believe they know the key drivers, key customers, and key performance indicators that support their business’s success. When managers are presented with information that does not support or contradicts their narrative, they can become resistant and hesitant to accept the insights presented. Often, they have biases they are seeking to confirm. Biases must be set aside, and managers must be trained on how to utilize data and information, trust the findings, and put them into execution. This is a cultural shift necessary in many organizations.
Management’s acceptance of information, particularly that which does not confirm their biases, is difficult, and not every organization is able to do this. Shifting this paradigm is a crucial exercise in the use of change management. It often requires a brave leader or sponsor to drive the organization, a lot of communication, and training on findings – backed by the data – to be conducted throughout the organization. When the organization can overcome these biases and trust the information presented, it becomes enabled to leverage data to drive change and improve performance. Without overcoming these biases, the organization may not progress further.
How SLKone Can Help
We at SLKone are firm believers in leveraging data to make informed decisions. Each of our team members is experienced and skilled in assisting organizations in establishing policies and procedures to enforce data integrity, assisting with developing and conducting analytics, developing presentable findings, and working with management to act on data and information. We have also helped organizations develop this competency internally by advising on system approaches, creating roadmaps for analytics and organizational structures, and coaching managers on the usages of analytics.
For example, a regional leader in specialty healthcare had invested in a data visualization platform to roll out dashboards and reports to their organization. In this process, however, the team did not tackle the shortcomings addressed in this article. These shortcomings included a lack of data integrity and understanding, failing to identify and define the needs of the business, and not recognizing the roles responsible for creating and maintaining the new platform and reports.
SLKone assisted the organization by defining appropriate reporting measures, identifying the critical data elements, understanding the data itself, and generating insights from the newly created reports. As part of the engagement, we trained the team on what to look for and how to critically assess their organization. We helped them cross the data-to-information gap and would be honored to help you too.