/ The expectations of modern data management — The New Dynamics of Data
The expectations of modern data management — The New Dynamics of Data
The role of data management is no longer solely attributed to the IT leader. Each division across any organization knows that data plays a huge role in successful decision-making. Data’s increased role has also led to increased requests for access to data, whether this means exporting bespoke reports or creating new dashboards. As each division leader across an organization looks to interrogate the data, searching for answers that might help improve their business.
The reality is that the expectation of finding the right answers without clear direction is too high — it can even be overwhelming. In the modern world, data no longer resides in the usual places — it now spans from your email, to your phone to ‘old fashioned’ spreadsheets. These pockets of dark data are often not integrated into BI and analytics — making it a completely untapped resource. The only way to uncover the potential, Is to ask the right questions to bring value to this data.
Therefore, the role of the leaders is to support the growth of the technical skills needed from everyday employees so that they can learn to understand where dark data resides and ask the right questions to gain value from it. This process speeds up business decision-making and agility.
The importance of context and asking the right questions
In episode two of Domo’s ‘Curiosity’ video series, guest Angie Schulke, Director and VP of Analytics at Lifetime, said she often hears people say: “I’m drowning in data but still flying blind.” — it’s an expression likely to resonate with most employees. Schulke and her team respond to this by guiding employees to tease out the right questions, like “What actions would you take if you got the right data?” and encouraging a conversation around outcomes. With a formed objective or desired outcome established, it’s possible to use tailored data to answer those questions.
Building data dashboards to support an objective can often just be the beginning. As employees consume the relevant data, it poses more questions, breeding data curiosity. This is precisely why providing the ‘right answer’ to an employee question can be a barrier to business agility and creative use of data. Domo’s Chief Strategy Officer John Mellor said, “It’s good to start with the business objectives or pillars, as this keeps you in the context of the overall goal.” The reason for this is that the tactics mapping to certain objectives can change. For example, many in-person industry events in 2020 had to be taken online at very short notice, showing how the tactics had to change. With the creative use of data and digital ways of working, it’s possible to achieve the original objectives.
Meeting customer expectations
Formulating a strategy from customer data is an ongoing process. The key element is whether you are meeting expectations. When used well, data can be a real breath of fresh air to an end user or consumer. For example, having preferences stored on a restaurant’s website will always be a ‘surprise and delight’ moment of the consumer’s journey. It acts as a strong engagement method and streamlined, personalized experience and promotes customer loyalty. The constant burden for vendors is to deliver those ‘happy moments’ exceeding the consumer’s expectations.
As more and more of how we do business is happening digitally, the process of curiosity has flipped. It used to be the case that IT leads would bring a data hypothesis to executives. Now executives know the power is in the data, and the process of requesting insight into certain areas is becoming more common, so much so that more and more investment is being made in self-service BI. A self-service approach means execs have access to live, certified data, allowing them to make decisions in the moment, whether this be insight into current marketing spend or quick profit and loss snapshots from the last week.
At Lifetime, Schulke encourages employees to become the customer, knowing the data they are giving away and thinking clearly about how they would want their experience to be improved as a result. This insight often uncovers unsuspected insight, as employees realize the areas of improvement through experience instead of forcing new processes without insight.
What is the difference between data and analytics?
When data undergoes analysis, there is often a desire to produce the best model. Data analysts will go above and beyond to create a brilliant new way to illustrate the data, but is it solving the business problem? The real goal should be how short the ‘time to value’ is. A concept brought to life by ‘Dude’s law’. A simple formula is that the ‘value’ equals the ‘how’ divided by the ‘why.’
Since its inception, the goal of BI and analytics was to answer big business questions with data. The next phase of BI evolution will come from the unknown — from moving past the silos, dark data, and other factors that make straightforward questions hard to answer. Data curiosity will spark the enthusiasm needed to help employees, partners, and customers put data to work in new ways. To do this, we need to make it easier and easier for people to ask questions of data, get the right answer, inspire more questions, and ask smaller questions.
Schulke outlined that this self-serving ‘fail fast’ approach can only be achieved through reusable data sets or data used regularly by employees. Encouraging a company-wide ethos of self-serving data analysis helps with business agility and productivity.
Achieving business objectives through data curiosity
During the pandemic, the companies exercised their data analytics muscles before the outbreak that have dealt with it the best, having already taken the first steps towards modern BI for all, which creates an environment of data curiosity. This curiosity can only happen through letting employees play with the data, encouraging them to continually refer to their business objectives as a reference point but to use data as a way of best achieving those objectives.
Therefore, it is the job of the IT leads and vendors to become the shopkeepers to data sets that are fit for purpose, ensuring data is governed, creating a safe sandbox environment. Once the source of all data is certified, all data sets provided act as one source of truth for the entire business.
Whether your business is facing global challenges, local disasters, or just everyday work concerns, understanding and managing data differently can help you respond more effectively. Find out more in episode two of our ‘Curiosity: Do Data Differently’ video series, which is available to watch here.