Leading with Data: Engaging Business Leaders (Part 5 of 9)
Leadership is the ability to establish and sustain a high-performing team and is usually the cornerstone resource for team efficiency and effectiveness. However, in order for this to be in full force, engagement should be the linkage between the leaders and the employees to produce a credible and well-founded team.??
For this session which happened last November 9, 2021, we had an interesting topic about Engaging Business Leaders wherein the discussion revolved around giving emphasis on how to engage business leaders in making data-informed decisions. We were so delighted to have the opportunity to be with a remarkable panel: Shujaat Ahmad, Director of the People Analytics - Future of Work at LinkedIn; Tim Peffers, Organisation and Talent Analytics Lead at Philip Morris International; Emma Woodthorpe, the SVP & CHRO of Mercury; Khurshid Anis, the VP - Sr. HR Business Leader of KeyBank; and lastly, David van Lochem, the CHRO of Group 42.
As a starting question to kick off the discussion, the speakers were first asked, alongside their personal introductions, on the underlying obstacles and impediments that prevent the business leaders from informing their decision-making process with data at work. One of the major obstacles they believe will hinder the business leaders in producing data-informed decisions is the gap in human resources. It is important that we identify the business problems before all else and delve into the possible approach in a way we can leverage data to solve these problems. By doing so, there should be the right people who are assigned to take this responsibility. And by means of “right people”, they should be exceptionally inclined and skilled to work with data. Hence, the failure to establish the kind of people to side into business governance is considered an obstacle in this field.
Following this, another obstacle they have mentioned is the quality of data wherein people do not recognize this as a problem. As aforementioned, it is much better that we always begin determining the business problems and then attempt to understand and translate them into what people’s data can accomplish. Afterwhich, the output will be combined with the other kinds of data sources. With the paramount purpose of formulating data-informed decisions, it is a must that we deeply understand what are the right uses we can do with the data we have.
In almost every truth that we know, may it be inclined to the workforce or not, there will always be myths that come with it. Even in the HR field, there are also prevailing myths thus the panel was given the opportunity to bust some of the biggest myths that are connected to this event’s topic. Firstly, understanding the fact that the absence of love does not mean the presence of hate. An example that was given by the panel is the contemporary phenomenon of the Great Resignation in which it was pointed out that we should not only focus on the causes of retention; rather, delve deeper into the ‘whys’. More so, another myth that has been addressed is that the capabilities of an organization will never surpass the power of its leadership. Among the many facets of decisions, 一 such as technical, financial, operational, and the like 一 the most important of them all will always be on the human capital decisions. If you have the right people who are handling your data, your company will be able to deliver better workforce results. At the end of the day, there will always be people behind every data; hence, human resources should be your biggest investment for success. Lastly, people usually share TMI or too much information about the data where in fact, making it simple is much better. If you really aim to make data-informed decisions, the more advantageous way is striking directly to the point. At times like this, less is more.
As the event continues, the discussion also gets to be more and more interesting. To live up to that momentum, the panel also shared their insights and ideas on the processes and ways of connecting business outcomes with people data in order to create a story that engaged business leaders. Most of them agreed that we should be able to identify the outcomes and business goals we are trying to attain. More so, it is also important to put the welfare of the employees first because they play a pivotal role in making the business or organization work. If business leaders do not value the welfare of their employees, they wouldn't be able to produce revenue thus could possibly result in the downfall of the business. Always remember that the human capital resources will always be the biggest investment in the company, hence, they should have the proper treatment they deserve in the first place. Make sure that they have access to a wide range of opportunities for them to fully ameliorate and enhance their skills. The bottom line is to learn to balance what works for the people and what also works for the business both at the same time.
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Having the right set of skills should not only be present in the employees but also the HR leaders as well. According to the speakers, the skill that must be embedded in the minds of these business leaders is the ability to understand and translate the data. As time continues to evolve, the data also becomes more perplexing; ergo, it is a necessary skill to be able to deeply comprehend and analyze the data available and translate them to the business. Furthermore, business leaders must also have statistical literacy in order to easily understand the financial facets of your business. Most importantly, leaders should be able to come up with problem-solving strategies.
In an organization, effective leadership is always deemed as the foundation of one’s growth and success. Having the right leadership, with the right person to lead, is necessary for the company to continue flourishing amidst the obstacles they might face. Nevertheless, good leaders know how to engage their people and utilize their energy to perform their best ability.
You may also check out the other articles on our Leading with Data series: