Every startup needs the ability to run on a tight budget, and frugal founders often find themselves lulled into believing that maintaining a strong data analytics and business intelligence (BI) operation is a luxury.
With investors and board members often pressuring management to justify every expenditure, it makes sense that you might wonder if you’re better off investing in data analytics until your company has reached a certain minimum size, or hit a particular milestone in its business journey.
As understandable as it is, this is a serious error. Every founder needs to remember that data is vital for every business, no matter how young your product is, and no matter how undeveloped your customer acquisition pipelines are. There’s simply too much to be learned from your data, even at this stage.
Indeed, data analytics allows you to:
- Map demand, track trends, and predict interest in your product, helping you achieve good product-market fit and keep ahead of the trends – instead of scurrying to catch up.
- Understand your target audience better, so that you can personalize sales and marketing, offer custom consumer experiences, and deliver better customer experience.
- Gain deeper insight into business processes to spot overlaps and redundancies, allocate resources more effectively, and make your business more efficient.
- Learn from both excellent and poor performance and reveal the reasons behind problems in your bottom line, so you can replicate past success and avoid repeating mistakes.
- Spot both opportunities and threats on the horizon – before you miss the chance to seize an opportunity or mitigate risk, so you can make better strategic decisions.
Even when new CEOs, CPOs, CTOs and CIOs do appreciate the value of data analytics, they sometimes think that their data requirements are still small enough that they can manage and analyze them manually. This too is a mistake. Your competition is guaranteed to be using sophisticated BI software already. Plus, it’s a lot better to bake analytics and business intelligence infrastructure and processes in from the start, and scale up as necessary, than to scramble to catch up later.
If you settle for manual data wrangling, you’ll never have the time to do it often enough or thoroughly enough. Understanding some basic home truths about automated BI and analytics tools is a must for founders.
Know Your Tools
You don’t need a whole data team to maximize the value of your business data; just the right business intelligence and analytics tools. Both business intelligence (BI) and business analytics (BA) benefit your startup, but you need to know which to apply to different circumstances.
You’ll use BI to explore historical data for insights into past performance, on a granular or a macro level. These tools help you to process raw data, spot patterns, and describe what has happened in ways that help you to understand it better, but they don’t produce explanations or predictions about the future.
BA mines your data to help you understand the causes behind past performance and predict future performance, trends, and consumer behavior. It uses predictive modeling to forecast risk and opportunity. You could say that BI is descriptive, but that BA is predictive. Both BI and BA self-service dashboards give you a better understanding of your business, your product, and your market to support your ability to make better business decisions.
Tools Alone Are Not Enough
That said, it’s not enough to have advanced BI and BA platforms. You also need the talent and ongoing training to use them effectively.
What metrics should you be collecting where? What types of queries and mashups will make the biggest impact? The best BI dashboard in the world will be a waste of money if no one knows which visualizations they need, and the most powerful BA platform will be useless if you don’t know how to understand its predictions.
A recent survey found that 56.9% of IT teams said their biggest challenge in applying BI was that they didn’t have the training to do so properly. It’s worth investing in decent analytics training so that you and your team know how to make the most of your advanced data tools.
Real-time Data Is Where It’s At
One of the main reasons why you can’t get by with manual data analysis for your startup is that big data is bigger than you realized. It can take a very long time to locate data in different sources, pick the datasets you need, normalize, standardize and migrate large amounts of data manually for analysis – long enough that by the time you’ve finished your report, the data is no longer relevant.
Information can be out of date after a few weeks for trend tracking; a few days for cybersecurity; and a few hours for fraud prevention.
You need real-time data harvesting, processing, analysis, and distribution, and only automated BI and BA tools can deliver it. Additionally, automated tools remove the errors that tend to creep in with manual data analysis.
Democratize Data from the Get-Go
Every department of your team stands to benefit from data analysis, from finance through to marketing and sales. HR, IT teams, and your executive leadership body all need data visualizations, insights, and predictions to make the right business decisions, improve productivity, and perform more efficiently.
Silos cut your employees off from data and handicap them from delivering their best. When you bake BI and BA teams, processes, and programs into your startup from the outset, you can ensure that there are no silos separating any departments from access to data.
Building self-service data analytics into the fabric of your organization allows every team to run reports and draw on insights as they need, without pestering IT for custom queries and reports. Also, make sure to draw on the right data. Less obvious data sources can be highly valuable – it’s not just about Google Analytics and your quarterly financial metrics.
Analytics and BI Are Crucial for Every Startup
Data is the new oil for every business at every stage, and startups are no exception. Building the right business intelligence and analytics platforms into your company and ensuring that everyone knows how to apply them removes silos and allows every team to process and analyze large amounts of data in real-time, fueling better business decisions and giving you the edge you need to keep ahead of the competition.
