What is Business Intelligence: A Guide for Startups
High performing founders and executives understand that data is one of the most valuable assets an organization has to operate their business. However, for startups, obtaining reliable and effective data to help inform key decisions can be difficult. In this guide we'll explore how Business Intelligence can transform your startup and how to best incorporate it into your organizations’ roadmap to maintain a competitive advantage and strategic progress.
What is Business Intelligence?
In today's fast-paced and data-driven world, gathering and analyzing information to make informed decisions is crucial for any business. That's why Business Intelligence platforms like Power BI, Tableau, Looker, etc. have taken off in market share. These platforms often get categorized as “data visualization” tools, but BI platforms provide far more than a simple dashboard, they can also serve as complex analytical solutions. Either way, the purpose of a Business Intelligence solution is to help uncover patterns, detect anomalies, and predict outcomes for organizations through data analytics.
BI platforms allow organizations to consolidate and analyze vast amounts of data from various sources, identifying patterns and trends that support strategic decision-making. According to Seagate’s Rethink Data Report, 68% of data within an organization goes unleveraged. This “dark data” is already being collected and stored in operational software, but many startups have a difficult time extracting the data and uncovering the insights buried within. As data continues to become the most valued asset in the world, the leading startups have begun making investments to leverage the vast amount of data they already own.
High performing founders are no longer content with a 45-day lag to get eyes on a static business performance report. Instead, they rely on real-time insights to make data-driven quickly and efficiently.
How can BI help scale my business?
As startups are increasingly shifting focus to profitability, it’s more important than ever that startups are efficient with their talent and resources. For many startups, it’s typical to get business performance reports (typically in the form of a month-end close) on the 15th of the following month, meaning decision-makers are waiting up to 45 days to get visibility into basic events that occur in their business. High performing founders are no longer content with a 45-day lag to get eyes on a static business performance report. Instead, they rely on real-time insights to make data-driven decisions quickly and efficiently.
When business intelligence solutions are implemented properly, it means decision-makers across the organization are aligned and are not operating off of their individual thoughts and opinions, instead they operate off what they collectively know to be true about their market, their business, and their customer.
Also read: 6 Use Cases of Business Intelligence for every Startup
How to Implement a Business Intelligence Solution
Many founders and executives don’t need convincing that business intelligence and data analytics add value to their startup. From ongoing management dashboards to acute analysis of customer behavior, the value of business intelligence platforms and strategic analytics are clear. What most founders need is a guide to get started. Unfortunately, our team has seen BI implementations go wrong too many times to count. That’s not to say it can’t be done effectively, but there are a few pitfalls you’re going to want to avoid. Here are some things you should devote your attention to:
Data Warehousing
Data warehouses are necessary to create a single source of truth within an organization and eliminate data silos. If you’ve ever dealt with the struggle of manually reconciling mismatched data sources together, then you’re familiar with the concept (or at least the pain points) of data silos. Data silos are created as each business unit collects data for its own purposes and are incredibly common with fast-paced startups as growing organizations are continuously adding new teams and software. You can eliminate your never-ending reconciliation between your disparate data sources by developing a way to centralize data in a well-thought-out data warehouse.
Business Intelligence platforms, such as Power BI, Tableau, and Looker, are not designed to be databases or data warehouses, even if analysts and BI developers try to use them that way. Although there may be a time and place to use BI platforms to aggregate siloed data, they should not be considered a long-term solution. BI platforms are designed to be supported by high performing data warehouses (Snowflake, Databricks, etc.), commonly managed by data engineers and data architects.
Data warehousing is commonly known for its ETL (Extract, Transform, Load) functionality. In order to have real-time insights on a dashboard, data needs to be Extracted in real time from the organizations operating software using ever-changing API’s. That data then needs to be cleaned and Transformed so that it can be customized to solve business needs and integrated with data from other operational software. Finally, the transformed data is Loaded into one of a number of different storage options to make it available for the analyst or BI developer to load into the BI platform. Your storage option will depend heavily on the type of data you’re storing and the use case of your analysis.
Talent
Another pitfall that startups fall into is not acquiring the right talent. An effective data solution requires some combination of data architects, data engineers, data analysts, and BI developers, depending on the scope of business needs. In an attempt to stay lean, many early-to-mid-stage startups try hiring a single person, expecting them to perform all the roles listed above. More often than not, this solo hire leverages the expertise they have in one area, but has to figure out the rest on the fly, building duct-tape solutions that won't scale. Errors begin popping up in deliverables and stakeholders don't trust the numbers in front of them.
Beyond making sure your team has the right technical skills, it’s equally important, and often overlooked, that your team has the necessary soft skills, such as understanding business scope and to communicating findings to stakeholders. This can save you from some frustrating conversations in the future.
Other Common Pitfalls
Founders and executives of startups should also understand that in-house BI implementations can be rocky and the path to progress isn’t always direct. Change is inevitable for startups. Switches in operational software can cause the need to rebuild or transition existing workflows. Employee turnover can also take a heavy toll on an in-house data team. Whenever someone leaves an organization, it can throw a wrench in workflows, but for a small data team within a startup, each member has a high amount of autonomy and responsibility, making it that much harder to overcome employee turnover.
This often causes a misalignment of speed and budget between stakeholders and data teams. Even if you get the talent right (I could even say, especially if you get the talent right), founders and executive have to understand that it may take 6-12 months before they get their first actionable takeaway, and the budget they see on day one is sure to balloon over time.
Alternative Solutions
There are other solutions for startups looking to get more insight into their business other than implementing an in-house BI solution. Consultants are solid options, although many are expensive and slow. We’ve seen consultants charge companies $80k for an 8-week discovery before they put fingers on keyboards to start building.
After witnessing first-hand the pitfalls that startups fall into and experiencing the widening gap between consultants and startups, our team of expert data engineers, architects, and BI developers decided to launch our own startup, SeedMetrics, a fully managed Business Intelligence solution designed to overcome these challenges and bring insights directly to decision-makers.
SeedMetrics uses pre-built connectors to your favorite software (such as QuickBooks, Salesforce, Stripe, etc.) to create plug-and-play interoperability across all your business data, allowing companies to knock down data silos and leverage real-time, cross-platform analyses. Our pre-built connectors, coupled with our industry leading data architecture, allow us to move quickly and keep costs low so startups can have a world-class solution that doesn’t breaking the bank, doesn’t sacrifice quality, and can still be customized to meet their exact needs.
SeedMetrics’ fully managed solution completely fills in the gaps within your data team. Whether you’re just beginning your journey into data analytics or you already have an analyst or data team, SeedMetrics will get you up and running in the matter of days, not months, and can 10x your existing teams output by helping them focus on what they’re best at.
We even went out and created pre-built reporting templates for your financial close, sales pipeline discovery, customer cohort analysis, and more, all of which are completely customizable to your needs. Try out our risk-free demo to see what types of analyses are right around the corner for your startup.
