As a Leader, how Do You Use Technical Data Skills for Data Leadership?
What you can do is create an organizational structure, workforce, and culture that give you an optimal chance to make the most of data. Read on to discover what you can do to create an organization that operates with data excellence.
As recently as five or six years ago, some organizations saw data handling solely as the responsibility of the IT team. It would be rare to find a business with this mindset today. Data has become something the most senior leaders and CEOs need to work with, handle, and communicate on. Solid data leadership enriches the information an organization can access and empowers everyone to confidently handle knowledge. When leaders are engaged with and responsible for data, they are opening the door for new opportunities.
Great leaders don't need to spend years studying data analytics to be able to implement positive data changes in their business. Instead, leaders need to be able to think about data - to be aware of how it is being used and to envisage how it might be used better. A working knowledge of good data science helps, but the ability to set strategic goals and assess the culture and climate for change readiness is more important. This means:
Leaders can help their entire organizations use data for business benefits by:
It may be tempting to think that employing a couple of data experts will revolutionize data, and it's true that bringing on some expertise in this area will make a difference. However, as a leader, you will also need to ensure that all of your senior staff members understand the need for dealing effectively with data. Managers and team leaders will know their teams and the business best, for they are your experts and knowledge owners. Managers and team leaders need to be engaged and contribute to identifying problems and opportunities that could benefit from a data perspective. It is these people who make decisions about what happens each day and understand best the requirements of their staff and their roles.
Listening and responding to the right people, on the right information, at the right time, is a fine art. When making important business decisions, you should rely on both the subject experts and what the data is telling you. The data alone will never give you a 100% complete picture and it rules out the opportunity for innovation and creativity. This is demonstrated perfectly in the following quote attributed to Henry Ford: “If I had asked people what they wanted, they would have said faster horses.” The best solutions often come from left field and through minds open to possibilities. Data specialists do not have all of the subject knowledge and years of industry experience that your staff will, and do not necessarily offer everything you need to know about what’s happening on the ground.
If you are in a leadership role and your business is one that is generating more and more data every day, you can show data leadership by questioning what is coming in. Ask the following questions to harness the true power of your data:
Using data for the best benefit involves truly understanding it. If you can’t make sense of the data you are receiving, there is room to improve how data is being captured, and for what purpose. Don’t fall into the trap of using data to justify the decisions you had settled upon earlier. Data can be used in so many ways, and in support of just about any notion that arises. Use the data to understand the operations, rather than to reinforce what you think you already know.
A 2016 McKinsey and Co survey found that structure is the most significant barrier that low-performing companies face when it comes to opportunities for growth through data. Creating an effective organizational structure enables better data effectiveness, including the creation of data roles and the involvement of business leaders in data management processes.
There is no single perfect structure for bringing data specialists into your organization. Data officers most often work in a centralized team, but there are plenty of businesses that deploy data experts around the business - in Marketing, IT, Customer Experience, or Strategic Planning. You might even consider pairing data experts within your HR or People and Culture section, given the importance of organization-wide responses to data work. Internal Communications and Training and Development experts can also help carry your data messages around the business.
Chief Data Officers are typically the most senior data experts on your staff. Chief Data Officers are responsible for creating and implementing a robust data strategy right across your business. They are often also responsible for creating your data policies and procedures and are tasked with ensuring data quality and security. Chief Data Officers need to have a high profile and be present around the organization, driving and delivering your corporate attitudes toward data strategy and approach. They may come with senior qualifications in operations, management, computing, risk, or legal.
Chief Data Officers may carry out roles very similar to a Chief Information Officer (CIO) or a Chief Technology Officer (CTO), though as the name suggests, the primary focus of a Chief Data Officer is the handling of data. CIOs and CTOs may deal with a more varied set of systems, including hardware and software.
Data Analysts work day-to-day dealing with data. They use various tools and systems to collect, clean, consolidate, and interpret data that can be used for the benefit of the whole organization. Data Analysts can help deliver on data strategy by working to ensure that data is accurate and presented in a meaningful way. Data Analysts can help your wider staff to work out what data they can use and improve how data is collected and stored.
Data Analysts typically come from academic backgrounds in operations, supply chain, finance, or technology and systems. They need to be able to focus on where the business is going and making improvements, rather than the retrospective study and analysis of data to date.
Traditionally known as data engineers, or even mathematicians or statisticians, Data Scientists are the highly technical people who study systems, processes, and reports. They deal with reviewing business processes, flow charts, decision trees, and data output sets. They also create logic systems behind the scenes that enable data to work effectively.
Data Scientists must have the ability to combine both technical and computational skills with the genuine function and needs of the business. They have often studied engineering, computer science, math, or statistics.
If you need everyone in your organization to be making better data-driven decisions, then it makes sense to consider data a team activity. You need to normalize data fluency and set the standard for expectations on how data is created, captured, and considered. Look for the team members who have educational or work experience with data or who seem to have natural fluency. They might have technical skills, which are important, but so too are the skills to communicate, to train, and to engage their teammates and colleagues.
Using data effectively also encourages collaboration. There are improved processes for information exchange, which in turn leads to opportunities for innovation. When data isn’t siloed, it can be disseminated and shared, and opportunities are identified and creative questioning can happen.
Data literacy and data fluency are terms used to describe how data confident an organization is. Data literacy is a great place to start. Creating a data-literate workforce means getting everyone to a good, solid base. Data literacy involves embedding the importance of data and empowering everyone to be able to manage their day-to-day use of data. In a data-literate business, there are standards in place to keep everyone working consistently. This means that the data professionals can spend their time on projects and advancement, without having to troubleshoot or work on the ground.
These are the levels of data confidence:
Dr. Brian R Spisak coined a new term for the framework created through his research - “computational leadership science” which involves connecting science and technology with proven leadership strategies. He has written about how computer technologies can inform and improve leadership practice, including strategies for improving morale and relationships even during remote work and connecting and coordinating “collective intelligence”.
Data can be used to improve aspects of culture:
The more data we use, the more we need both strong and strategic leadership, paired with sound advice from data experts. Finding the right solution to enable this growth in tandem is part of the work to be done. Pimcore is a data solution that provides quality data from multiple streams. It is used across a variety of industries, with big-name customers including Gant, Burger King, and Beam Suntory.
Pimcore helps solve data challenges by managing information generated from multiple sources, including records related to products, customers, employees, inventory, suppliers, and sites. It brings data together and consolidates it, reducing the need to assess data from siloed and scattered sources.
Pimcore drives innovation through its open, flexible, and scalable structure, which can be deployed on-premises or in the cloud. It is flexible and can be integrated with many other commonly used sites and applications. Pimcore can enable transformation through flexibility and capacity for automation. It is a multi-function solution that can grow your revenue by being intuitive for staff and through the provision of rich digital experiences for customers. Contact us to learn more about what Pimcore can do for your business.
Why is data governance critical in small to medium-sized business?
A robust data governance model or framework is critical in all businesses, even small and medium-sized ones. Getting data governance right, even in the early days of operation gives you the best chance of growth in the longer term. Data governance enables you to mandate your information consistently and establish rules and guidelines for data handling. It also reduces the risk of inaccuracies and inefficiencies becoming part of the norm.