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Data-Driven Decision-Making

How To Be A Better Leader – Data-Driven Decision-Making

Being A Successful Leader Means Knowing Your Audience As Well As You Know Your Product. Data-Driven Decision-Making And Information Analytics Have Forged A Path For Insightful, Modern Operational Strategies—So Why Are Businesses Still Struggling, And How Can You Avoid These Pitfalls?

  

The World In Data

In the modern business landscape, there is an exponentially budding field that has dominated the minds of many marketing teams, business leaders and company cultures themselves. Thanks to soaring advancements in technology and global business acumen, firms are holding data, analytics and information in the highest regard—even above their current operational strategy. The gap between the decision-making process and the knowledge or basis of judgment to support those deterministic decisions closes faster than ever. Companies are learning quickly to leverage the mounds of data that ebb and flow across physical devices, digital consumer touchpoints such as email marketing campaigns or by pulling from historical data.

This innovative new method of intelligent business analysis has established a precedent for the fusion of marketing and logistics. By utilizing raw numbers and statistics, effective leaders may bolster their brands’ trust, infuse their operations with facts over gut-feel decision-making and drive revenue growth by slashing overhead, reducing wastage and powering sustainable efficiency.
The problem is, even with access to the best analytics software packages or data quality in the world, nothing will happen if the ultimate decision doesn’t reflect what the data says and, therefore, the reality of the situation.
Investing in analytics and data-driven strategy is rendered useless—even detrimental—unless you and your employees are also as fully invested in the complex decision-making process.

 

More Data-Driven Marketing Related Content from HVMA:
► The Future Of Personalization in Digital Marketing
► Using Identity Resolution To Create A 360-Degree View Of Your Customers
► Cambridge Analytica’s Huge Data-Driven Plan Gone Bad

► Omnichannel Marketing – The Ultimate Marketing Pathway

 

*Connect with us on LinkedIn HVMA Social Media LinkedIn Profile
*More Data-Driven Content from HVMA: Are you ready to get a ROI from social media?

 

Think about this—right now, within your firm, there’s probably at least one person who is making a baseless decision that goes against the data—mined or not—and which is costing you and your business hard-earned revenue. Think about how expensive that data may have been to collect to possibly be considered in that decision, and how cheated you now feel about the whole ordeal—puts things into perspective, doesn’t it?

Bi-survey reports that less than 50% of companies agree with the idea that information is treated as a highly valued asset within their organization…so then why do two-thirds of them believe it will be in the future? Quite counterintuitive, isn’t it?

Of the companies polled in the study, only a third are currently utilizing information to optimize their business’s operations and predict future trends.

Stop waiting for something to happen—the data exists, here and now, and so do you! You should not fear data, but rather seek to understand it and how to procure it. Remember—with the initial realization of data-driven approaches came the onset of robust software technology solutions. These tools, working tangentially with social media platforms or your own omnichannel marketing approach, can do much of the heavy lifting for you. Opening the doors of data to your team in a collaborative-style, educational-oriented environment. Your organization’s effectiveness will remain only as good as your weakest link! And as an executive decision-maker, that responsibility lies with you.

By expansively equipping your teams with the faculty for data-driven decision-making and working closely together through data democratization, an even balance can be achieved between the objectivity of raw qualitative data and the intuitive nature of human instinct. Keeping a handle on both judgment and analysis can yield boundless growth for a company that knows the truth beneath the surface!

 

What Data-Driven Decision-Making Is, And Why Not To Fear

Data-Driven Decision-Making, or DDDM, is the process that involves the collection and parsing of data pertaining to user audiences or potential/return customers from various online and physical sources. This data, based on quantifiable goals and key performance indicators, or KPIs, pulls information from patterns and metrics which deliver real-time transparency into the factual nature of operational goings-on. Data-Driven Decision-Making centers around the premise of continual and consistent growth.

If companies can track their long-term progression through educated short-term movements, keeping your empire’s ship afloat through the maddening flux of the digital terrain becomes a much more manageable task.
Adaption is key to survival, particularly as volatile markets rise and fall by the day.

Whether your bottom-line is taking losses or your customer base’s tastes begin evolving, you can maintain a monitor on the pulse of your business and take actionable steps to ensure success. Develop these understandings into cohesive strategies and tangible activities that can stimulate consumer traction and push you and your firm towards your goals. Companies have been shooting in the dark for long enough…it’s time to work smart, and not hard!

It’s a no-brainer at this point: everybody knows that data speak. A study by MIT Sloan School of Management professors Andrew McAfee and Erik Brynjolfsson unveiled that amongst companies surveyed, those that primarily data-driven saw 4% higher productivity and 6% higher profits. More and more companies are resorting to multi-channel business approaches to locate their audience, attract them into the sales funnel and secure conversions.

However, statistics reveal that most modern leadership is ignorant—almost fearful—of the implications of accepting the reality of the results. On average, organizations tend to only use around 50% of the information data available to make decisions, and over 58% of survey respondents claimed their businesses base at least half of their operations decisions on “gut-feel” rather than using data that reflects the facts.

It’s much easier to sink back into traditional styles of management, refuting the objective insights gleaned by marketers into your customer’s 360-degree profile. Plus, it’s virtually impossible to peruse through all the massive reams of data regarding each customer—let alone the collection, extraction, formatting and procurement of meaningful information from these raw data blocks. Even so, this process remains essential to providing your firm with an accurately relevant direction.

We tend to forget that humans evolve practically just as much as our world evolves intricately. As such, data science has not forsaken us with powerful software tools to support the sifting and movement of huge data volumes.

BI software suites empower business execs with the knowledge and technical prowess to locate, extract and glean deep-rooted insights. This has drastically reduced the necessity for siloed IT expertise which doesn’t translate across all company teams.

Now, just like with an iPhone for photographers, these modern data management solutions have torn down the walls in facilitating empowered employee teams. Your supply chain division can work seamlessly alongside R&D or the financial department to manage data in bite-sized pieces, render charted reports and produce visual presentations which transform disorienting data pieces into digestible, actionable plans.

So now, why fight it? If the objective of business intelligence, or BI decisions shifts towards providing personalization and unique brand experience to curious leads or fanatical repeat customers, the key remains in uncovering their needs and truly understanding what they need, before pitching your product or service. This eliminates the messiness of the sales process and directly addresses problems with relevant solutions. We’re making it loud and clear: listen to the data!

 

 

Decision Makers 101: Why You’re Afraid Of The Data

In the face of overwhelming information, many business leaders and their firms falter. Here, we explore some of the major reasons and explanations for why over half of all companies are struggling to onboard the data-driven approach, and what your brand can do to avoid these traps and stay true to your goals while nailing the performance targets you need to!

 

Data Location: The first and foremost reason for the misuse or lack thereof of information as the foundation for a data-driven decision-making infrastructure lies in the information apparently not being available—or at least, that’s what the companies say. The reality is a little more reassuring; reliable information does indeed exist, but the hiccup appears in actually locating the information.

Many firms lack a coherent and accessible framework to manage and consolidate the data collected. As HBR puts it perfectly, “They’re like libraries with no card catalog and no covers on their books.” The manifestation of social media channels and proliferation of universal smart technology has only exacerbated the difficulty in efficiently managing the diverse ranges of analytical metrics, to the point where less than 44% of employees can admittedly find the information they need.

Data Quality: Another huge mistake which companies can blunder into while trying to manage their data and user information is the inherent quality of the data they collect.

Datapine borrows the Thomas C. Redmann definition of the term, which is “the condition of a set of qualitative or quantitative variables, that should be “fit for its intended uses in operations, decision-making and planning.” Data quality management can determine the difference between true mechanical insights, or a fabricated illusion borne from carelessness.

Within each stage, from acquisition to maintenance, to data democratization within the company, accurate and meticulous data management are crucial to even beginning to ascertain the state of your firm. Poor data quality, as the second most notable barrier to data-based decision-making, speaks volumes about data governance as well—meaning, who the designated data “experts” within the company are…and why they shouldn’t necessarily be the only ones with that knowledge.

 

Data Governance/Collaboration: Data governance is just that—who governs, or has oversight and manages, the vast piles of historical user data which teems beneath a company’s feet. They are the gatekeepers of the data, and the decisions that follow.

This happens to also be one of the heaviest and most complex issues within Data-Driven Decision-Making. Historically, top-down management approaches were the dominant style, encompassing 39% of companies who employ it. The other 34% compromise of management committees and the remaining 18% are democratic, or collaborative in nature. The catch? 69% of the respondents in the Bi-Survey study admit their company would perform better with stronger collaboration, and the top-down organizations feel they lag behind their competitors’ performance because they use a data-driven approach (when the real culprit is systemic).

HBR believes too many business leaders are delegating the job of data analysis to the IT or finance departments and believe even themselves to be too fearful to trust their own ability to manage and manipulate data. The good news is, that doesn’t matter. The bad news is, your own misjudged “lack of expertise” is invariably fulfilling your worst nightmare: leaving you perpetually uninformed and willfully ignorant while the available answers swim around right under your nose! Your investments in data are yielding weak returns due to the underinvestment in the data’s comprehension.

The method to solve this lies in hiring individuals who are well-versed in education as well as they are data experts, so they may understand the flow of information and convey it to other organizational departments in a comprehensible manner. Hiring experts who can’t transfer this knowledge vertically through your firm aren’t worth investing in anymore, as they may be highly skilled but can’t train everyone else to make similar use of the analytics methodology.

 

Data Biases/Past Reliance

One of the worst things to do to your own business is stifled its growth by latching onto the past. By halting or hindering innovation and focusing on what’s behind you, only missed opportunities will occur. Sure, we would like to follow historical recipes for success…right? No. The markets and digital scopes around us are in a constant state of flux, and so too, must you and your brand remain—adaptable and flexible to the incoming trends and new approaches necessary to resonate with audiences.

Another aspect to cognitive bias is getting tunnel vision—focusing too much on vanity metrics such as likes, views, and SEO. More “likes” are great, but what does that really translate to in terms of profit margins and revenue? How is that even calculable, and what can you as a manager do to uncover the underlying story behind the numbers?

Exploring subjective data-driven decision-making leads us to more issues, such as what is known as “cooking data”. This term has less to do with a tasty meal, and in fact describes the destructive process of injecting decisions with confirmation biases through the data being observed. Good data shouldn’t be rigged to support your plan or necessarily be swayed in any particular way; objective and accurate measurements are critical towards Data-Driven Decision-Making success.

These types of cognitive biases, intended or not, occur routinely. They can influence business leaders to subconsciously ignore the truth within the data and chase after a certain desired result. Remember, as Neil Patel, social media marketing expert explains poignantly: “Good managers can make bad judgment calls by offering data only to justify their decisions.”

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