This is the first of a three part series on data-driven organizations.
Using data as a central pillar of strategy at all levels of an organization often requires cultural shifts that can be challenging. But, organizations who can overcome these difficulties stand to leave competitors far behind.
Cultures that characterize themselves as data-driven find benefits in:
- Strategic decision-making
- Operational efficiency
- Financial controlling
- Customer service
- Regulatory compliance
- Customer account management
- And more
Efficient, strategic collection and analysis of data can provide a huge advantage, but it doesn’t come easily.
We’re going to start with a look into the struggles that are holding many companies back, including executives who insist on following their gut instincts, concerns about data sharing among departments, and technical issues like outdated platforms.
We’ll close by offering three steps that will allow your organization to start putting data at the center of strategic conversations.
Executives Struggle to Adopt Data-Driven Mindsets
In a 2012 study, the Economist Intelligence Unit surveyed 530 senior executives from around the world about the role of data in their organizations. Nearly half of the respondents (46%) indicated that strategic decision-making benefitted the most from a data-driven culture, yet many executives continue to struggle with modeling this desired behavior.
Depending on the age of the business and the professional history of the executive, the report’s authors point out that the “transition to a world in which the smart decisions are data-driven” can be consummately difficult “for an executive who has built a career on smart, instinctive decisions.”
But striving to embrace this evolution is crucial for executives and the organizations they run.
A 2015 survey conducted by The Economist Research Unit in partnership with ZS Associates reported that companies that benchmark themselves highest on profitability and customer engagement show extensive collaboration between executives and analytics professionals.
Only 41% of the 448 senior executives and professionals who responded to the survey said such collaboration existed at their companies, but 55% of those who rated themselves highest on profitability and customers engagement cited close ties between executives and analytics.
Torsten Bernewitz, a principal in ZS’s Princeton office who specializes in managing organizational change, summarized the problem of analysts this way:
“We don’t fail because we get the analysis wrong, we don’t fail because the analysis isn’t precise enough and we don’t fail because the insights we present are weak. But we do fail when the decision makers ignore our conclusions or, perhaps worse, misunderstand or twist them. If this happens, we have failed our audience and our mission.”
Privacy, Security, and Data Hoarding Issues
While executive attitudes can delay the adoption of data-driven strategies, technical concerns around sharing data can also hinder efforts.
Specifically, the EIU survey found that about one-third of the companies surveyed were grappling with privacy and security concerns that arise when data are shared. Approximately the same number named, “a reluctance by department heads to share data” as one cause for their failure to achieve a data-driven culture.
Privacy and Security
For many companies, the fears about data security are well-founded. If they’re relying on legacy systems that were created ten or twenty years ago, there may indeed be reason to keep things locked down.
Modern SaaS tools, however, should come with fully configurable privacy and security settings that allow organization-wide access to data without endangering either security or privacy.
SurveyGizmo, for example, allows for complete customization of access at the group or user level. Embracing (and managing) the necessary shift to software that’s designed to empower more users to employ data in their day-to-day work is vital for companies looking to take full advantage of the massive flows of data that are available.
Data Hoarding and Silos
After analyzing its survey results, the EIU concluded that companies that have successfully implemented a data-driven culture share four common features:
- They place a high value on sharing. Companies own data, not employees. Data are a resource that can power growth, not something to be hoarded.
- Shared data is utilize by as many employees as possible. In practice this often requires rolling out training on an as-needed basis.
- Data collection is a primary activity across departments.
- Buy-in from top executives is crucial. Without it, little will change.
We’ve addressed that last point already, but notice how the first three deal with the free flow of data throughout an organization.
Employees and executives alike can be threatened by the democratization of information; they may feel that proprietary access provides them with job security. But this type of data hoarding, whether at an individual or departmental level, cannot be allowed if we hope to put data at the center of each and every strategy.
Executive Champions Set Data Free
One of the most effective ways of overcoming both infrastructure and attitudinal obstacles is to appoint a strong executive sponsor.
Change management consultancy Prosci reported that “active and visible” executive sponsorship has been a major factor in a project’s success since they began collecting data in 1998.
During 2016, nearly three-quarters of projects (72%) that were led by extremely effective sponsors succeeded, while those led by very ineffective sponsors met with success only 29% of the time. As companies invest larger and larger sums into analytics and data collection, it becomes increasingly vital to have strong leaders overseeing their adoption.
In his Forbes article on executive sponsorship, Brent Dykes, Director of Data Strategy at Domo, tells the story of one digital marketing VP who seemed to fit into the “effective” category. But, as the data came in and revealed how poorly certain marketing channels were performing, he, “tended to disappear and ignore his stated priority. Rather than working with his analytics team to address performance issues, his silence and inaction sent a clear message -- he was a data pretender, not a data believer.”
Just as high-level executive commitment is an absolute must for spreading data-driven strategy throughout an organization, we must choose the right “boots on the ground” to spearhead its integration into teams and departments.
3 Steps to Join the Data Elite
Now that we’ve seen where many groups stumble on the road to data-driven domination, it’s time to talk about avoiding these pitfalls.
Dominic Barton and David Court have worked with dozens of companies in data-rich industries, and they’ve found that, “using big data requires thoughtful organizational change.” They suggest focusing transformation efforts in three areas:
- Develop business-relevant analytics that can be put to use. Focus on collecting data that’s in sync with your day-to-day processes and current decision-making norms.
- Embed analytics in simple tools for the front lines. The key, Barton and Court argue, is to separate the statistics experts and software developers from the managers who use the data-driven insights. Managers need intuitive tools and interfaces (we respectfully suggest SurveyGizmo’s Team Edition) that help them with their jobs.
- Develop capabilities to exploit big data. Even with the most easy-to-understand tools and data models, most teams will need an analytical skills upgrade. Culture and mindset need to change to make analytics part of the fabric of doing business. This may require training, role modeling by executives, and/or the use of incentives and metrics to reinforce behavior.
Data Can’t Hold Things Together on its Own
Data can solve a lot of business woes, but the shiniest tools and most sophisticated data models in the world won’t shore up an organization that’s adrift without vision and strategy.
“CEOs should see vision, data-driven strategy, and leadership as a three-legged chair,” says Ronald VanLoon. “Without any one of the legs, the chair falls down.”
Tune in for the next installment in this series, where we'll talk about how to move from using data to drive large scale strategic initiatives to testing market viability for products and concepts.