While data is a valuable resource of the modern world, not all data is equally valuable. Businesses have become adept at collecting and storing raw data, but relatively few take the necessary steps to refine and analyze what they have collected. It is in analyzed data that the most important insights can be found, yet only 24% of executives have managed to create a data driven organization.
What keeps this percentage so low? Other companies may want what data driven organizations have, but a mix of factors keep them from achieving it. Some 36% of executives don’t rely on data to make decisions, limiting support for improving its analysis. Even those who want to improve can’t do it with will alone. 70% of executives lack a clearly defined data strategy. Rallying workers behind a vague notion rarely leads to desirable change. Some firms struggle with data quality and access, running into untrustworthy datasets and siloed data being unavailable for use. Worst of all, the majority of workers can’t tell the difference between good and bad data. Only 21% of workers believe they have strong data literacy skills. True data professionals are in high demand, and most companies have to struggle to hire and retain one. Given all these obstacles, it is no shock that up to 73% of all data within an enterprise is spared even minimal analysis. What use is data that never sees refinement?
The obstacles listed above don’t only pose frustrations. They are also risks to the company’s bottom line and future. Poor data quality leads to, on average, $15 million in annual losses. Such drains on revenue manifest in several different ways. Poor data quality and analysis casts a clouded lens on an organization’s vision for the future. Faulty data can cause poor decision making as businesses pursue misguided business strategies. The result of these failures tends to be less productivity and growth on top of missed opportunities. Sometimes customer relationships suffer as well.
On the other hand, businesses are empowered when they have a solid understanding of purpose, partner support, and the appropriate tools and processes for the job. They can compare risks and opportunities side by side. They can use what the data tells them to develop product innovations and marketing strategies. Data can even help companies manage their relationships with suppliers and customers alike. All of these benefits reflect themselves in the financial numbers. Data driven organizations are 178% more likely to outperform in terms of revenue and profitability.
What are the signs? How can you tell if your company needs help with data analytics? Consider a few different things. How long do you spend waiting on data to come in before making important business decisions? Many business actions are time sensitive, and poor data practices can cost you opportunity. Is all company data in one place, or do different departments follow their own procedures? Collaboration is difficult when two departments use separate systems. How does your organization measure progress or success? A measure wholly lacking in objectivity makes internal evaluation difficult, and every business must be able to evaluate itself if it is to grow.
If you are not content with your answers to the above questions, perhaps you should consider if Google Analytics 360 is right for your business. Depending on the quality of your current data tool implementation, Google Analytics 360 may help you do more with your data. Understand that an enterprise tool will not fix a bad implementation and/or configuration. Migrating from another platform to Google will cost more time and training than if you were using Google to start. The companies that benefit the most from this service seek integration with other Google products. They want sophisticated analysis of hit level data and must make constant daily or hourly marketing decisions. Also, possession of a large dataset requires them to rely on sampling.
Google Analytics 360 offers many features and benefits. An investment in 360 allows for advanced tools like BigQuery Export, Data Driven Attribution, and more. Enterprise training and support is readily available. New data can be accessed in under 4 hours, and 360 supports imports of both 1st and 3rd party data. Sessions are nearly unlimited, with data not subject to sampling after 500,000 sessions. Perhaps most notably, Google Analytics 360 is partner first, bringing an expert team with the purchase of a license.
How should your business go about choosing a partner? The first thing to check is technical expertise. Every business has a different set of needs, and knowledge of one system does not guarantee success with another. Before choosing a partner, ask to see a sampling of their work with other clients. Look into their experience in your particular industry. Check reviews and references from other clients. Confirm their certification in all platforms you may be using.
Once expertise is determined, there are some practices and expectations you should look for in an analytics partner. Make sure they charge according to outcomes, not by the hour. Have them deliver regular customized training sessions for your entire organization. Look to them to contribute simple, actionable ways to leverage data and its platforms. Keep up regular meetings to ensure you receive insights when they are needed. Data is a treasure trove, but its gems must be cut and shaped before being put on display. The right partner helps businesses do just that.