In today’s data-driven world, businesses are constantly looking for ways to use data to gain a competitive advantage.
A Horror Story
Imagine it’s Monday at 6pm. A Slack message from the Head of Analytics to the Chief Digital Officer pops up: “Can you jump on a call? We’ve got an issue.” Most of your C-Level team, a product manager, and the VP of Engineering are on the call. Whatever it is, it’s clearly urgent.
The Head of Analytics says: “We are not going to hit our quarterly numbers and our Top Line numbers are soft. We had no idea we were off track. What should we do?”
What happens next will determine whether your company rises to the challenge and meets the quarterly numbers… or gets slammed by the street in the coming weeks.
Missed Signals and Poor Decision Making
Your business is filled with decision points. Big (like this one), medium, and small. Decisions are the basic unit of Digital Operations. Why did this happen? How did we miss this signal? What do we know? What do we not know? How do we leverage the information now? How much analysis and deep-dive is needed before we can act? What we decide and why it leads us directly to what we do and how well we execute together.
Most leaders sense that while their teams are smart and capable, they’re not consistently efficient decision-makers. Yes, decisions are being made, but are we getting the right inputs / signals? Are we holistic in our understanding? Are we fast enough? Is our reasoning consistent?
“If you also have these anxieties you’re in good company – 98% of operators we’ve talked to are dissatisfied with their company’s decision speed and efficiency.”
“McKinsey Global Institute reports that data-driven organizations are 23 times more likely to improve customer acquisition, 6 times more likely to retain clients, and 19 times more likely to increase profits! “
We’ll discuss some of the challenges businesses face when trying to be data-driven in both strategic and operational decision making and how to overcome them.
1. Missed Business Performance Opportunities, Issues & Green Shoots (Unknown unknowns, Unknown knowns):
“Less than a third of direct-to-consumer businesses perform weekly performance checks of key KPIs”
One of the biggest challenges in being data-driven is the sheer amount of KPIs and metrics to be monitored. In most cases, changes in sales are missed altogether, or detected too late. This is often due to a lack of insights into customer engagement issues, product performance blind spots, green shoots, leakage, slow-moving changes, and trends.
To overcome this challenge, businesses need to prioritize the most important KPIs, establish metric governance and use analytics tools that provide reliable real-time detection and alerting for product metrics.
2. Long time to decision (Known unknowns):
“Insight-driven businesses are growing at an average of 30% each year; they take greater than $1.8 trillion annually from their less-informed industry competitors.”
Another challenge in being data-driven is the time it takes to make decisions. This is often due to a lack of insights and a common canvas to resolve issues. The typical tools of choice are dashboards that neither drive insights nor decisions. Businesses often have too few analysts and too many asks, which can result in decisions being made using partial or missing information or gut feeling. To overcome this challenge, businesses need to prioritize the most important decisions and use analytics tools that provide real-time insights and alerts.
3. Manual Last Mile Analytics:
“Only the Top 1% have the requisite data teams and tooling for large scale metrics automation.”
Others do not and continue to be manual. Another challenge of being data-driven is the over-reliance on analysts and data scientists to generate insights. Many businesses invest heavily in self-service analytics platforms. These platforms are rarely self-serve in insight generation and in most cases used as glorified spreadsheet generators. The lack of automation in generating insights and the need to manually monitor dashboards can lead to missed signals, a significant waste of time and resources. To address this challenge, businesses need to invest in analytics tools that offer advanced automation capabilities and integrate with their existing systems.
4. Data Analytics Costs/Labor:
“More than 50% of analyst time is spent answering & diagnosing “What happened last week? Last month?
And Where?”
Finally, being data-driven can be costly in terms of tooling and personnel costs. There’s a high computational cost to enabling comprehensive diagnosis over the high-dimensional, high-volume data, in addition to building your data infrastructure for processing and analysis.
Data teams are often a significant cost to organizations, and answering “what changed” is an afterthought with the existing tooling. In addition, a significant amount of time is spent in fire drills (~20%), and leaders and teams need to spend lots of time manually monitoring dashboards. To address this challenge, businesses need to invest in analytics tools that offer advanced automation capabilities and provide real-time monitoring and alerts.
“Data analytics makes decision-making
5x faster for businesses.”
Flying Less Blind
Next time you’re out with your colleagues and sharing the latest professional fire drills, notice how many of them originate from one of these 4 challenges. I’m surprised how prevalent it is across industries, experience levels, and job titles. Very bright, well-intentioned people fall prey to these all the time.
In conclusion, being data-driven is crucial for businesses looking to gain a competitive advantage in today’s market. However, it comes with its own set of challenges. To overcome these challenges, businesses need to prioritize the most important KPIs, invest in analytics tools that offer advanced automation capabilities, and provide real-time monitoring and alerts.
By doing so, businesses can turn their data into a valuable asset and gain a competitive advantage in today’s market.
This is a many part series, and we will dive into each of the topics in subsequent posts.