Do you know what your business should be measuring?
If you said “no,” you're not alone. 54% of businesses say that BI is essential to their operations, yet the majority of companies struggle to use their data to make better data-decisions, and according to Forrester, only 22% of available data is being used.
BI provides the potential for businesses to develop much deeper perspectives by bringing in context from multiple systems. However, understanding BI data takes time, experience, and expertise. It's not just about the technology; it's a fundamental business change.
Keep reading to see how working with an experienced BI partner can give you an edge.
Experience Saves Time
Your organization’s data is often spread across various systems and platforms. It resides in the cloud, and on premise. This is where the data model comes into play.
Business Intelligence is powered by data models, so it's vital to get this right. If BI software can't act upon the data model, then it's as good as useless.
For an inexperienced data team, the process of collecting, processing and cleansing data can be overwhelming; the ability to bring together and mediate executive perspectives from across a business can often be fatal.. Your data “coming out party” that you thought would take a couple months can quickly snowball into years.
This is where the value of an experienced data team can be leveraged. A team that understands which data modeling to use as well as which ETL process is more likely to give a good blend of efficiency and value. An experienced team can automate this task and get you actionable data in weeks, and can use industry peer benchmarking and personal experience to help diffuse contrarian points of view and align perspectives to the benefit of the organization.
Experiences Adds Context
Let’s say you have access to a mountain of data. But you now have so much data that it's easy to get buried in detail. Ergo, one of your biggest strengths has quickly become one of your biggest burdens.
The problem is that data alone is useless unless it provides accurate context. Take, for example, the following:
Clearly this is correlation without causation. This same issue is all too common with business intelligence.
This happens when businesses are missing essential “storytelling” elements. Let’s say the chart above, instead of representing drownings and Nicholas Cage films, reflected sales revenues and expenses. You’d likely look at it and deduce that revenues and sales are correlated.
There’s a good chance that you would be right, but why? Which expenses are good expenses, and lead to more sales, and which expenses do not? What is the incremental impact of a single transaction on your bottom line? How can your team’s actions impact outcomes and start driving the black line far above the red line?
The answers to these questions lie in the context - the “why” not the “what” - that leads to the results seen on a chart.
Experience plays a crucial role in understanding what data points to look at and what business decisions can be modified to impact the results. Understanding the context requires an understanding, therefore, of both the technology - what data points to bring together, and how - as well as the business - why are the numbers what they are, and what can the business do about it?
Experience Builds Trust
Let’s go back to the graph above, but this time let’s assume that you saw it for what it was - an interesting correlation without any causation. So you ignored it.
But what if it wasn’t drownings and Nicholas Cage movies, and instead was revenue and costs. And instead of representing results from the past, it was instead showing predictions of future outcomes - derived from complex machine-learning algorithms that you don’t understand.
Do you simply ignore it because you don’t trust the numbers? Do you ignore it because you don’t understand the algorithms?
We’re not saying you should or should not trust everything your data is telling you. But we can say that the world is littered with companies who didn’t trust their data - and didn’t act on it - and some of them are no longer with us. Kodak. Blockbuster. And many more.
The point is not that data doesn’t lie, it’s just that it can be difficult to evaluate and compare it without a thorough understanding of how the numbers are derived. An experienced data partner can help verify, validate, and benchmark the data process, and ensure you’re not acting on bad data, and demonstrate the logic of acting on data that others have found to be reliable.
Experience Makes Technology Better:
Machine Learning and Artificial Intelligence
Even though machine learning has been one of the most impactful developments in BI over the last few years, business intelligence will always have an essential human element.
Machine learning engines can produce some really powerful stuff, but without an understanding of what the desired outcome should look like, businesses using machine-enabled analytics to drive decision making may be going down the wrong path without even realizing it. Machine learning, ungoverned, can create an automated way of reproducing the same bad actions as those being performed by their human counterparts.
The benefits of machine learning in business intelligence are limited by what end-users can do with the output. Not only do users have to understand what the output is telling them, they have to understand what actions - what inputs - need to be changed or optimized to achieve the desired business outcome.
A truly valuable BI partner will be able to leverage the capabilities of machine learning by guiding both the technology and the people using its outputs down the right path. An experienced BI team will also help your organization build trust in the data and an understanding of how to impact it. And that BI team will work side by side with you to transition and effect the change and outcomes that you are looking for.
There are thousands of external influences vying for our attention all day every day - and data is no different. You can’t expect that just because you have subscribed to a cutting edge business intelligence solution that your team will automatically adapt it to optimal effect.
Data visualization is more than just a slick and attractive user interface. To be effective it needs to display the right information, at the right time, and in a way that is easy and intuitive for your end users.
For example, at Grind Analytics, we focus on Quality, Quality and Efficiency as the bedrock for measurement, because it aligns with core business competencies. Every touchpoint gets a comprehensive assessment with a goal of establishing actionable KPI’s that help quantify activity and drive optimized action. Core KPI’s are served up in powerful, easy to comprehend scores and reports that help ensure your team can make the right choice, every time - which has provided our clients enormous lift to their bottom line margins.
There is no out-of-the-box solution on the market currently that can do this out of the gate for your unique organization. There are several providers offering up colorful dashboards and templates, but they aren’t going to automatically filter and sort the myriad of data visualization elements specific to each user. And they always suffer from a limited amount of customization capabilities.
An experienced data partner with expert data model competence can help you create the data perspectives and the associated visualizations to make data consumable and actionable for your team. This requires an understanding of how people work, and balancing the human and machine capabilities to avoid data overload. Make sure you work with a service provider that has in-depth understand of data, technology, and the specific business problems impacting your industry to find the best way to attack and achieve your goals. You will save yourself months if not years of development time, and start delivering the results you need to become a market leader.
Schedule a demo today and find out how BI should be done.