However, data presents potentially dangerous downsides that are largely misunderstood across organizations. While having helped numerous clients across fifteen industries effectively using their data (from Fortune 100s to startups), I’ve only seen a few that were truly sophisticated in terms of organizational-wide data integration. The large majority were on the opposite end of the spectrum (despite many contrary claims).
KPMG found that 84% of CEOs are concerned about the quality of the data they’re basing their decisions on. This concern is undoubtedly justified, but it only scratches the surface in terms of the issues that most organizations face with their data.
There is no such thing as “bad data”. Issues stem from bad processes, poorly structured teams, departmental siloes, and almost always a lack of collaboration and guidance from leaders who will use the insights to make important strategic decisions.
Gartner measures the average financial impact of poor data on businesses
at $9.7 million per year. I’ve personally seen bad processes and lack of cross-departmental integration cost a company millions due to misleading and inaccurate information.
The costs go beyond the financial implications; missed opportunities can impact the customer experience, business reputation, new products/services or other revenue streams, and operational efficiencies.
It is imperative to start with the key business question(s) that you want the data to answer, rather than just collecting a bunch of data to analyze and hoping the data team will stumble upon some magic insight. This requires a data-driven culture.
A data-driven culture starts with leadership, who must be intimately involved for an organization to embrace the potential upside data offers (and avoid the dangers data presents if not properly integrated).
This doesn’t mean that the CEO is expected to know the technical elements of data analysis, but too often leaders hire analysts or a data team without strategic integration or process development and think they can sit back and wait on results. This couldn’t be farther from the truth.
The typical analyst rarely if ever sees the inside of the boardroom or makes critical decisions. They lack the knowledge and experience required to translate objectives into research questions that will positively impact the business.
It is the responsibility of an effective leader to make strategic decisions and then translate them down to various constituents throughout the organization. This is especially critical with such a comprehensive yet nuanced resource such as data, which can drive operational efficiencies and effectiveness across departments but can also have a negative impact.
Many Fortune 500 companies have begun hiring someone in the “C Suite” to lead this role, most often in the role of the Chief Data Officer (although titles and job descriptions vary). This is a great first step, but this is a far cry from solving the problem. Many more steps are needed to mold the organization into one that is adequately data-driven. However, if this person has the ability to blend strategic business thinking with organizational data infrastructural needs, and has access to the key decisions and issues facing leadership (usually directly reporting to the CEO or COO) then this can be an excellent hire for someone who can be a true change agent for the organization.
Unfortunately, this is a lot of ‘ifs’ and contingencies that rarely play out, instead falling victim to the next initiative once the ‘data box’ has been checked. NewVantage Partners recently found that 77% of Fortune 1000 executives surveyed report challenges with their businesses adopting big data and AI initiatives. This number is up from 65% in 2018, showing a significant increase in the realization around the challenge implementing this in their business despite significant investment.
These issues continue to persist despite 55% of the companies surveyed spending over $50M – and 21% spending over $500M – on big data and AI initiatives!
Further, respondents say that this isn’t a technology problem – it’s an issue with people first and processes second, making up 95% of the reported issue. Technology only constituted 5% of the problem.
The lessons learned from these large corporations are just as important for smaller businesses, who have significantly fewer resources to aim at data initiatives (but hopefully have less bureaucracy to contend with as well).
Regardless of company size, it is critical for the modern leader to embrace and understand data and the potential impact on their organization. Fusing these analytical chops with the executive’s experience and existing skills (leadership, strategic business knowledge, decision-making capabilities, access across departments, etc.) put the organization in a highly desirable yet rarely achieved position.
This isn’t a magic bullet scenario. Data is critical to every business, but to make it work in your favor requires a data culture. Building this culture around your decision processes should be intentional and will take time: time to build the right team, time to ask the right questions, time to collect and preprocess the “right” data, and time to implement the insights the data science team has derived.
Used effectively, data can create sustainable growth or transform you into a market leader…but the opposite is also true. Data will only answer the questions it is asked. Leaders must ensure the right questions are being asked, the right talent is in place, and that the organization comes together to use it effectively throughout.
John-David McKee is the CEO of Ins & Outs, a data-driven strategy company. Learn more atwww.insandouts.org.
