What do you think about your agency’s use of data? Your answer should be anywhere from a warm “fairly well”, to an enthusiastic “we’re smashing this”, then you are doing better than most.
It seems strange that data analytics adoption in modern workplaces should be so difficult. It is becoming more common to talk about Big Data, algorithms, or AI in our culture. These terms are most commonly used by people in the street or have at least heard of them.
Research shows that people don’t accept the importance of these technologies in their daily lives. According to the Harvard Business Review, “data-driven” is a term that is less common in businesses.
It’s not enough to expect your employees to adopt data and analytics. If you want your agency to embrace a data-driven culture, you must be intentional about it.
Why do you need a Data-First Culture?
It’s easy for everyone to lose sight of the deliverables when they are all focused on their work. There is so much to do, it’s easy to get too focused on the next thing.
In an organization that values data, it is natural to stop and reflect. Analytics is used by data-driven agencies to determine what works and what doesn’t. This information is then used to make strategic decisions. They replicate good practices and throw themselves at what’s not working.
It’s simple in principle. It’s a simple approach that is effective. Gallup’s recent research showed that companies that use customer behavior data outperform peers by 85% in terms of sales growth and 25% in gross margin.
Many organizations have difficulty getting people to embrace data and analytics, despite the potential benefits.
Why Do Companies Struggle To Make Analytics Stick?
This dilemma is familiar to anyone who has ever switched between phones with a different OS. It feels awkward; everything is in a new place. It’s frustrating to feel that you can’t just use it to do your day.
It all boils down to the same issue that is causing analytics adoption problems. People are put off by difficult, confusing UIs. People are put off learning a new platform. People are put off by programs that don’t work well with their existing tools.
Despite all the efforts of software developers to make BI easier, it still doesn’t work. Despite all the technological advances that are supposed to make data easier for everyone, people still resist. The potential of a new era in data analytics has yet to be realized by human psychology.
Some developers have attempted to make analytics more intuitive and simple so that they can be integrated into users’ existing workflows: embedded analytics.
What’s Embedded Analytics?
If a platform can generate reports and visualizations from data, it is called embedded analytics.
It is designed to work with users’ natural workflow and make data readily available in a context that suits their needs. It can provide users with all the information they need to react quickly to changing circumstances. However, it can also give insights that can be used to prevent future problems. It is easy to use because it is part of the systems and platforms users already use in their daily lives.
This last point may seem like an obvious consideration to encourage analytics usage, but don’t underestimate the impact of ease of use on user adoption. For best results, embedded analytics must be well-designed so that they fit seamlessly into users’ workflows. Ashley Kramer, Sisense’s CEO, wrote that many people unknowingly draw insights from data every day and use them to benefit their lives. Smartwatches for example use data to inform us when it’s time for us to get up and move around to reach our daily step goals. Many of our favorite apps and products make the process of extracting data seamlessly, and sometimes even invisible. Because the data is right where we need it, and in the right context, it’s so easy to use.
Users will adopt analytics if it is easy and frictionless to access and if the data is relevant and clear to their current work.
It will be difficult to create a data-first culture without the right analytics interface. However, embedded analytics can be applied in a way that allows users to gain insights quickly and easily.
Everybody has some analytical streak. Who doesn’t want to see tangible proof that their hard work pays off? You just have to find the tool your team enjoys using.
How to unite your agency with a Data-First Culture
We know that analytics is more intuitive when it feels like part of a person’s workflow. This is especially true when they are short on time and need quick answers. This is why you should examine the workflow of your team and assess whether it supports your analytics goals.
The risk of decision fatigue is higher if your tech stack includes multiple, single-purpose tools. Each tool has its embedded analytics, which increases the risk of decision fatigue. Jumping from one platform to view resourcing information to another to examine project financials to another to review task times estimates creates more friction for the user. This is also important: none of these data can interact. You may need to use another tool to put it all together.
The first step towards creating a data-first culture is to unify all the work streams into one platform. This will make your life easier and give you one source of truth for all your data. This will mean that you won’t need to use another spreadsheet in your daily life (unless you have to).
Once you have established these facts, it is easy to add analytics to the picture by simply embedding them into this platform. The forecast is an example of a platform that can do this easily. Forecast’s add-on for advanced analytics, AvA, puts powerful, completely custom reporting capabilities at the core of your workspace. The forecast provides all the tools you need to plan, manage, and track financials for your projects. It also integrates with your CRM system and allows you to manage your resources.
Data is of no practical value. Data is only valuable when it’s analyzed and used to make informed decisions. Analytics won’t be of any value if your team doesn’t engage with it. It is worth investing in creating a data-first culture. This will allow you to present analytics in context and make it more accessible to your team. It will make a big difference in how your agency works and in your bottom line.
