Building Expert Teams for Successful Data InitiativesAn Expert Team Is More Than a Team of Experts
Brian HenryDirector of Solutioning
The necessity of an expert team that can deliver successful data initiatives has never been more critical. This can be quantified just by looking at research regarding the cost of poor data alone. Gartner found that the average cost of poor data quality on businesses amounts to roughly $10M to $15M annually while at the macro level it cost the US an estimated $3 trillion per year. Poor data quality comes in many forms, but some examples are duplicate records, incomplete data, or inconsistent formats. These data quality issues must be resolved to be able to deliver accurate and effective reporting and analytics. The need for a group or team that can deliver not only a quality data platform but deliver business value from such a platform continues to be essential for businesses.
Of similar importance as data quality is the need for data literacy within an organization. As a data initiative progresses and data becomes an organizational asset there must be an ability to understand and communicate regarding data. According to Gartner, by 2023 data literacy will become an explicit and necessary driver of business value. The ability to speak “data” throughout the organization, not just in IT, is essential to the adoption of data literacy and competency to ensure your initiative delivers business value. Delivering on all this is where things get more complicated as the ability to find the right people and form the right teams to translate value from data remains a continuous challenge. While Gartner states that 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency, they continue to see big data initiatives fail at a rate of more than 60%. We believe this is due to a diminishing of true data and analytics experts assigned to projects as well as client stakeholders on the business side challenged with communicating exact needs. A data project must be a well thought out and heavily supported business initiative for it to deliver business value. It takes a solid partnership between the business and technical teams to build data literacy as a competency within an organization in order to result in the delivery of a successful platform.
Delivering successful data initiatives begins with the setting of a vision and building an expert team that consists of individual experts each doing their part as a cohesive group. You do not want to get caught with a team that is not able to deliver the envisioned or desired results. Hiring or building a team that cannot execute or may not have the technical competency to handle a data initiative will cost companies precious time and money they cannot afford as the need for data literacy becomes more necessary to maintain a competitive edge. Building an expert team is a process that begins with effective leadership, encompasses clear planning and communication, and utilizes crucial collaboration to deliver results. The steps listed here are essential for managers and project sponsors who seek to build expert teams for their most strategic initiatives.
Expert Leadership: Leadership is a key aspect of creating and forming an expert team. You must have someone who both has a solid business foundation along with a broad and somewhat deep understanding of the data-centric technical environment. The ability to spot, bring on, and develop true data experts who will be able to meet the key deliverables of a data initiative is a key factor that will have a significant effect on the future outcome. Leaders must create an environment for experts to be their best and do their best work. They must be able to pull optimal performance by generating energy and enthusiasm in the team to perform at a high level. They must set the project vision and clearly and consistently communicate that vision. A clear and consistent vision will ensure the appropriate roadmap will be set forth making the desired outcome possible.
A recommended strategy is to hire an outside consulting team who already has a high performing team intact with the ability to provide the necessary leadership skills and experts to deliver on a data initiative. The right team will showcase an experienced talent pool and have a history of success for these specific strategic initiatives. For example, one company had a failing project because they had hired a team who did not have the core competencies to deliver on the project objective. An expert team was able to step in by request of the project director that was sponsored by the CFO and successfully delivered on multiple project phases while generating significant business value that was envisioned at the start of the project. Here’s what stood out in this scenario – the importance of executive sponsorship and continuous communication amongst high level stakeholders from multiple areas of an organization that are part of data solution adoptions as they are designed to deliver the intended business value.
Expert Purpose/Scope: The commitment to deliver on the vision set forth by leadership provides a solid foundation for success. The scope of a project must be clear and understandable by the group and they must see the impact the initiative can bring to the company. This is true whether it is an internal project and even more when contracted out to an external team as there is additional incentive for the successful completion of a consulting project. The project requirements are a key driver to being able to set the deliverables or features that make up the scope. This is where you need effective business stakeholders and business analysts who can deliver concise business requirements that can be turned into a clear and specific set of deliverables. It is also essential you have a product owner or program manager who can bridge the gap between the needs of the business and an appropriate technical solution to deliver on those needs. This is most often the biggest miss with a data initiative and as stated previously is the cause of the high failure rate that exists among these projects. They also need to be able to leverage the strengths of each member of the team. A team is only as successful as each of its parts and being able to utilize the team appropriately can be extremely impactful on delivering on the overall scope. In one case, we had a client that due to the cohesive teamwork of the business product owner and the project team that welcomed our ability to automate processes that saved the business hours of manual work each month. If you can pull the right group of leaders and experts who can effectively determine the scope and create a sense of purpose, we have seen time after time successful implementations that deliver high business value.
Expert Planning: Another essential aspect of delivering a successful data initiative is proper and effective planning. Once the scope has been set, a cohesive process of delivery is required. The first step is to break down the deliverables and utilize chosen experts on the team appropriately. There are multiple approaches but utilizing both aspects of work breakdown and a delivery process such as agile methodology can be extremely helpful in ensuring deliverables are being met. Incorporating both deliverable-oriented and process-oriented work approaches will help hone complex project scope into smaller achievable steps. The process starts with features planning and then the sub-grouping of tasks that can be completed on a shorter time cycle. Planning must be an iterative process as may occur with data initiatives that experience changing priorities and scope due to shifting prioritization and requirements. Another necessary factor in planning is having a program manager who can leverage the strengths of each member of the team. This means there’s a focus on ensuring you are placing both individual team members and the team in a place where they can succeed. It’s important to breakdown the work into deliverables, have a delivery process that will set the team up for success, ensure the appropriate leveraging of each member of the team, and this will lead to on-time delivery of a successful data initiative.
Expert Collaboration/Teamwork: An environment of effective collaboration is necessary to deliver on the goal of a data initiative. This means focusing on cooperation and letting experts do what they do best. Whether it is during requirements gathering, architecture design, development, or testing, the key is to generate a collaborative environment where experts can work together bouncing ideas off one another to deliver the best solution for each deliverable. Clear and concise communication between team members leads to a smooth process of meeting deliverables and creating a platform that delivers value. To encourage brainstorming and provide spaces for discussion on challenging the status quo are the steps it takes to create an environment for innovation. Unified teamwork paves the way for consistent collaboration and teams that operate at this level are far more successful.
In closing, the combination of effective leadership, setting a clear consistent vision, keeping open communication that leads to effective collaboration, and trusting your experts leads to a highly productive team that will deliver on the proposed strategic projects. Expert teams require expert leadership and teammates that can collaborate in unison to deliver on the overarching goal. Though an expert team may be a premium service investment, the decision is worth the effort and will pay dividends through increased productivity and successful delivery. An expert team can help build a culture of excellence that leads to high performance that supports the strategic goals of the company. Successful data implementations require a relationship of trust built with a data partner as a prerequisite for the completion of your next data initiative.
About the Author
Brian Henry is the Director of Solutioning at Expert Analytics where he works with clients to match technology and process solutions to business objectives. He has 10 years of planning, development, and deployment oversight experience with data analytics initiatives at global companies where he interfaces directly with C-suite leadership. In addition to program management responsibilities, he works extensively with developers and end users to refine information access, availability, and delivery formats.