Today’s business leaders largely recognize the importance of embracing analytics and implementing data-driven processes. However, the conditions necessary to truly take advantage of data aren’t built in a day and must be nurtured – selecting the optimal data strategy demands careful consideration. The right direction will transform a business into one that can capture data, analyze that data to highlight the actionable insights hidden within multitudes of red herrings and then successfully follow through on putting those insights into action.
A smooth data adoption process may go as follows:
– A company introduces a new method of data collection.
– The IT department discovers a way for this data to provide value and changes its practices to maximize the advantage.
– Soon enough, other departments and business leaders catch wind of this success and begin integrating that available data into their own activities.
That’s the ideal (although still uncommon) scenario. In practice, obstacles abound, and many businesses don’t have as easy an experience. Too often, decision makers underestimate the value of data-informed decision making, and analytics reports go ignored. In other cases, the problem is actually too much data, as overwhelmed managers have trouble determining what information to focus on, and poor analysis means “data insights” are based on partial information and lack validity. This oversimplification of data is a common issue as decision makers require streamlined data to support decisions – but often, in the process, miss the forest for the trees.
For advice, I consulted a panel of data experts on how businesses should best approach data and build a successful data analytics strategy. The experts I spoke with offered these eight tips:
1) Encourage data adoption by valuing human input.
Engineer James Barbee advises earning goodwill among employees and leadership by offering a clear understanding of how analysis is conducted. Knowing how data is collected and how insights are arrived at make the results a lot easier to trust and rely upon. Employees should feel empowered and augmented by data, not shackled or replaced by it. Be sure to communicate that data is there to complement and enhance existing processes. At the same time, construct models with iteration and refinement in mind, ready to be further optimized by new information. Data can reach some strange conclusions if models become decoupled from actual human behavior. Keeping analytics grounded by human input will not only ease adoption, but can also improve the quality of insights.
2) Inventory your data.
Jon Baker of Wire Stone points to the value of clearly understanding your data sources and your capabilities to leverage potential new sources. Once you have a full view of your own data, consider the possibilities that may be offered by data belonging to the companies and services that support your business. Third-party data is a powerful tool that can go a long way toward a business’ growth.
3) Fill gaps in your data and analytics capabilities.
Mark Donatelli of VML advises that valuable data can be gleaned from public and free sources – which are often overlooked but can nonetheless provide key information. It’s also important to assess available analytic tools and resources and ensure they align with what is needed to achieve business goals. Any recognized gaps should then be addressed.
4) Prove what data can do by beginning with a specific focus.
Ed Falconer of Rosetta recommends starting the data adoption process by focusing narrowly on smaller issues in order to demonstrate a quick win. This is an effective method of building goodwill and proving the value of data within the organization. It’s easy to become overwhelmed – and fail to recognize actionable insights in a timely manner – when attempting to capture every single data point relevant to a business. Starting with a small scope is the best way to get the data adoption snowball rolling.
5) Break complex questions into smaller pieces.
Falconer’s advice on accomplishing larger goals a piece at a time extends to how data should be used to take on complex issues within a business. Ed recommends building a roadmapping tool called a data decision journey, detailing each specific leg of the path toward implementing a working analytics strategy. It’s important to define the problem the business needs to solve, and then break it down into the steps and smaller problems that need to be solved in order to achieve that ultimate goal. This process should include sketching out the major decisions to be made in order to determine the correct courses of action and matching these to the data points that will inform those decisions. In the end, this roadmapping provides a valuable approach to handling issues otherwise too sizeable to digest strategically.
6) Hire experts who can make data tell a story.
Kiran Goojha of the Association of National Advertisers points out the need to make analytics not just understood but persuasive. Winning over executive decision makers requires deft storytelling, and businesses thrive when they have individuals with these skills.
7) Make data visual.
Donatelli supplements the advice that data needs to tell a story with the suggestion that, if properly visualized, no more storytelling is needed. Alternatively, storytelling and data visualization can be used hand-in-hand to communicate analysis with optimal clarity.
8) Offer data-driven thought leadership.
Brian Rafferty of Siegel + Gale points out the opportunity to utilize data not just for internal decision making, but to enable a business to act as a thought leader. Data has the power to recognize key trend and pattern details that business’ customers are often eager to learn about. At the same time, it serves businesses well to demonstrate both this knowledge and their capabilities to address customers’ needs around these trends. The ability to provide insightful thought leadership is a decisive business advantage that a successful data strategy ought to develop.
Each of the experts I consulted agreed that the commitment businesses make to data analytics needs to be more than a financial investment – to really succeed it must also be cultural and practical to their needs. When a business truly embraces data, believes in its potential and pursues a sound, thoughtful strategy, data can serve as a competitive advantage and a force capable of transforming almost all aspects of the business for the better.
Cheryl Metzger is the Strategy Director at Wire Stone, an independent digital marketing agency helping transform customer experiences for global Fortune 1000 brands.
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