The term ‘strategy’ gets thrown around a lot these days. Some even say it’s a buzzword and you’re drinking the Kool-Aid if you still use the word. We happily will play the devil’s advocate on this dispute and confidently say that this word still has a place in an organization when used appropriately. Appropriately being the keyword here…
Unbuzz the Buzzword
According to the Oxford dictionary, a strategy is a plan that is intended to achieve a particular purpose. We like to describe a data analytics strategy as a master plan or a game plan. If you don’t have a game plan for your analytics, how do you intend to leverage your executive analytics solution to the best of its abilities, so you can successfully reach goals and maximize ROI?
Let’s Get Down to Business
You would never play a game of chess without some sort of strategy and implementing data analytics software should be no different. A data analytics strategy will help you create a centralized single source of truth and this needs to be led by someone, usually the project’s executive sponsor. It is an overall vision for how to collect the data and then how that data will be used to guide business decisions. It provides clarity and helps teams focus on what data should be analyzed for actionable results.
An analytics strategy outlines how to deploy data throughout an organization. It determines what metrics to focus on, how to lay out dashboards, what details are important for decision-making, and who should have access to them. In short, a data analytics strategy is the how, the who, and the where to deploy your high-level data that deliver value throughout the business.
Two Roads: Which One Will You Choose?
Once the strategy is created, it obviously then needs to be implemented and from our years of experience in implementing Domo Business Intelligence (BI) software, we generally see clients take one of two roads.
Road #1 – Give everyone in your organization the power to produce reports. Otherwise, known as self-service.
At the surface level, you might think this is the best approach because then everyone has free reign to dig into the data as they choose, explore information relevant to their role, be curious about other data, and use their unique skills & abilities to make decisions. Unfortunately, we’ve seen this have the opposite intended effect. Successful implementations are definitely not where the average person of the company is building dashboards with their own KPIs whenever and however they want.
The self-service approach tends to lead to a bunch of disconnected and duplicated reports or a bunch of useless dashboards that are all sharing the same KPIs but with different numbers. It also commonly leads to no one tracking the same actionable KPIs. This all results in ineffective decision-making because data-driven decisions are made on incompatible and conflicting data.
Road #2 – An organized approach with defined metrics and structured rollout.
If you want to become a future-ready company, the 2nd road is the path we recommend. At a high level, the sponsor (or another C-Suite executive) defines the metrics and then rolls those out to the different management levels below. This is generally the most successful in our experience. This invites discussion around what metrics & KPIs to monitor and track (which we highly encourage), but at the end of the day, the final decision is deferred to one C-Suite executive member. The dashboards are then built for each department or level so that they are all tracking the KPIs relevant to their role’s decision making, but also connected to the other departments & levels decision making. This is the best way to have actionable dashboards that can quickly leverage all of your data. For an example of this, check out our article on how actionable dashboards work in a senior living organization.
We find that the first road is a common trap companies fall into because, as Kevin Larrivee, an Executive Analytics Consultant with BT Partners describes, “Clients often feel everyone is smart enough and can build their own dashboards.” While we’re super happy you feel that way about your staff, it’s important to know that in the steep learning curve of adopting or moving to true data analytics software, just because you can write code doesn’t mean you can create the best dashboards. Kevin continues, “A good strategy is reigning everything in and creating a single source of truth, which is your data analytics strategy.”
Data Never Sleeps
The global Internet population grew from 2.5 billion in 2012 to 5.2 billion in 2021. That’s almost double in less than 10 years. It’s pretty obvious then that businesses today are flooded with an incomprehensible amount of data. If you can’t figure out how to effectively control the immense amount of data in your business from the top down, your staff risk being overwhelmed and losing sight of important tasks and trends that help to reach your goals.
An overwhelming majority (89%) say analyzed data is essential to their organization’s innovation strategy today. So, what happens when you fail to efficiently analyze the data your business will lack innovation and adaptability, while also falling short of creating a strong competitive advantage. All of which will ultimately dissolve an organization.
It’s simple: the more strategic you are with your analytics, the more you know. So, what do you think? Do you think ‘strategy’ is still just a buzzword? Although many people flout the word around a lot these days, it’s only natural for it to lose some of its steam, but that doesn’t mean it shouldn’t have a place in business, especially your business data analytics.
If you have questions on how to build an effective analytics strategy for your new (or your previously deployed BI software that sadly isn’t yielding the outcomes you’ve hoped for so far), contact our Domo experts who will provide you with a little analytics strategy boot camp, so you become truly data-driven.
