Uber owns no taxis, yet is the largest taxi company in the world. AirBNB owns no real estate, yet has the most accommodations in the world. These companies run their businesses on data, and lots of it.
Data is king, and it is only becoming more important. Proper analysis and utilization of data helps to uncover the what, the why, and even predict the future. As a result, data must be a core component of your digital strategy.
Hindsight
At the most basic level, data gives us hindsight. A simple example is how grocery stores utilize loyalty cards. Customers sign up for them with some basic personal information, and in return the store gives the customers discounts when they use their card. Data collected from these cards helps the grocer identify individual purchasing habits -- it gives them hindsight.
This is why online retailers encourage customers to create accounts. The data collected (which products are being viewed, which terms are being searched for, etc.) all help track what is happening in their store.
Insight
Understanding the "what" is just the basics when it comes to data analytics. Having the view into the "why" provides insight.
Why do certain customers buy one product over another? Why do certain products sell better at certain times of the year? These are the types of questions the data can help provide insight into.
Hindsight
At the most basic level, data gives us hindsight. A simple example is how grocery stores utilize loyalty cards. Customers sign up for them with some basic personal information, and in return the store gives the customers discounts when they use their card. Data collected from these cards helps the grocer identify individual purchasing habits -- it gives them hindsight.
This is why online retailers encourage customers to create accounts. The data collected (which products are being viewed, which terms are being searched for, etc.) all help track what is happening in their store.
Insight
Understanding the "what" is just the basics when it comes to data analytics. Having the view into the "why" provides insight.
Why do certain customers buy one product over another? Why do certain products sell better at certain times of the year? These are the types of questions the data can help provide insight into.
Foresight
Being able to predict behavior is the next step; this is where the most positive transformation can occur for an organization.
Again using grocers as an example, stores can use big data to predict and suggest the price points of certain products at certain times to ensure the right amount is in stock and fresh. If the price of strawberries, for example, is too high grocers risk having too many in stock and the strawberries going bad. If they accurately predict the right price point, they can keep the right amount moving off the shelves at a pace that ensures each package is still fresh.
Lastly, there are some scenarios where proper data analysis can actually help to prescribe some actions. In other words, using data can help make things happen.
Let us use the car company Fiat as a fictitious example for this. If Fiat mined the publicly available social media posts specifically looking for terms which suggest a propensity to buy their car, they may be able to help drive more sales. The scenario could go something like this: John Smith posts to Twitter, "Thinking about buying the new Fiat. Can't decide between that or the Toyota Prius." That post will get picked up in Fiat's social media scanning algorithm, and alert the salesperson in John's region to contact him directly. That contact may help to influence John in purchasing a Fiat.
Making it happen in your organization
To leverage data effectively, naturally you need data. Determine the sources, and if none exist start setting up your data collection processes.
Once you have the data, it needs to be usable. Having it in 25 disparate systems will make life tough. Rather centralizing it and "cleansing" it for use (i.e. ensuring accuracy, removing duplicates, etc.) is key.
Additionally, data can help create a source of revenue. Identify any data which may be unique to your organization which others externally may pay to access. Ensure proper usage controls and governance are in place.
Also keep in mind potential external integrations or partnerships.
Ultimately, there are endless possibilities to how you can utilize data. Start small, take an MVP approach, and build from there as you learn what works for your organization.
Being able to predict behavior is the next step; this is where the most positive transformation can occur for an organization.
Again using grocers as an example, stores can use big data to predict and suggest the price points of certain products at certain times to ensure the right amount is in stock and fresh. If the price of strawberries, for example, is too high grocers risk having too many in stock and the strawberries going bad. If they accurately predict the right price point, they can keep the right amount moving off the shelves at a pace that ensures each package is still fresh.
Lastly, there are some scenarios where proper data analysis can actually help to prescribe some actions. In other words, using data can help make things happen.
Let us use the car company Fiat as a fictitious example for this. If Fiat mined the publicly available social media posts specifically looking for terms which suggest a propensity to buy their car, they may be able to help drive more sales. The scenario could go something like this: John Smith posts to Twitter, "Thinking about buying the new Fiat. Can't decide between that or the Toyota Prius." That post will get picked up in Fiat's social media scanning algorithm, and alert the salesperson in John's region to contact him directly. That contact may help to influence John in purchasing a Fiat.
Making it happen in your organization
To leverage data effectively, naturally you need data. Determine the sources, and if none exist start setting up your data collection processes.
Once you have the data, it needs to be usable. Having it in 25 disparate systems will make life tough. Rather centralizing it and "cleansing" it for use (i.e. ensuring accuracy, removing duplicates, etc.) is key.
Additionally, data can help create a source of revenue. Identify any data which may be unique to your organization which others externally may pay to access. Ensure proper usage controls and governance are in place.
Also keep in mind potential external integrations or partnerships.
Ultimately, there are endless possibilities to how you can utilize data. Start small, take an MVP approach, and build from there as you learn what works for your organization.
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