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May 22, 2018
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Ideas to Implementation – Identifying the Right Data Strategy to Find Success

Last month we had an incredible DataWorks Summit Berlin! This marked our sixth year in Europe, and the event featured 1,200 attendees from 51 different countries. The theme was “Ideas. Insights. Innovation.” which focused on how leading enterprises are using advanced analytics, data science, and artificial intelligence to transform the way they deliver customer and product experiences at scale.

Two of the keynote presentations on mainstage helped hammer home the “Ideas” message.

The Single Most Important Formula for Business Success

On day one we heard from Hortonworks CTO, Scott Gnau, on how data fits into today’s business strategy and how enterprises need to shift their thinking when driving business transformation to deliver the best customer and product experiences. The key take-away from his session was important equation: Data Strategy = Cloud Strategy = Business Strategy.

This key point is why all the technology and innovation talked about at Summit is so relevant. These three strategies need to be aligned for an organization to achieve success over the long-term. Thinking about them separately will inevitably lead to issues.

When it comes to an organization’s data strategy, the importance can’t be overstated. Data is the lifeblood of companies. The sheer volume of data growing daily creates a prime opportunity to figure out how to capture and leverage data for the business. This strategy entails more than just analytics, it encompasses capturing, streaming, and managing the entire life cycle of data.

This data strategy touches every industry, from mobile device manufacturers that leverage data to impact customer relationships and drive business models, even to businesses such as farming. Smart manufacturing leverages real-time sensor data to improve quality, visibility, customer engagement, and manage yield and cost. Additionally, smart cities help connect disparate data to improve quality of life, reduce cost and improve the user experience. Data capture and connection in real-time is making the difference in all these areas.

These new connected devices and types of data make cloud much more relevant. Now, some data lives its entire lifecycle in the cloud instead of a data center. This means businesses need to link their cloud strategy to their data strategy. Some benefits of cloud include business agility, no upfront cost, and the ability to experiment and create new use cases. These advantages are key for driving business, which makes it paramount to connect our business strategy to both your cloud strategy and your data strategy.

You can watch the full keynote, here:

Big Data Success in Practice

Another keynote presentation from day one featured internationally best-selling author, Bernard Marr, showcasing the top five big data use cases as well as some of the biggest mistakes to avoid. He was able to bring an interesting perspective and share stories from a variety of industries of how they have implemented big data, including companies like Google, Walmart, and Disney all the way to a local butcher shop.

The five big data use cases he touched on were as follows:

1. Informing Decision Making- Using data both strategically and operationally to help make better decisions across the whole organization. Data access with self-service is a big challenge. To do this, there needs to be different structures and flatter organizations so more people can make data informed decisions.

2. Better Understanding Our Customers– Need to gain a 360-degree view of customers, including what they’re doing and buying in the future. Organizations need to find new data sources and need more data diversity.

3. Improving Our Customer Value Proposition– Build smarter products and services by integrating data analytics capabilities. Some businesses used to try to hide what data is being collected and not alert you when changes happen. GDPR is positive, it benefits customers and increases trust.

4. Automating Key Business Processes- Driving efficiencies across your operations by automating various business processes. Some examples include analyst reports written through machine learning, dynamic insurance premiums based on tracking in an app, and voice analytics in contact centers to find truth or lies in claims.

5. Monetization- Using data as an asset we can sell that drives the value of our businesses. Examples of this include John Deere with self-driving tractors, drones monitoring crop conditions, and sensors picking up soil conditions and making recommendations to increase crop output.

One of the most fascinating examples from Bernard’s presentation was about gaining a better understanding of customers. He talked about a butcher shop that wanted to learn how to better tailor their marketing messages and gain insight into the conversion rates of customers walking by. To gain this information, a device was installed in the window of the shop that could pick up Bluetooth signals from the smartphones of people walking by. No personal data was transmitted, but by tracking the Bluetooth signals, the butcher shop could see how many people walked by and how many people went inside. This gave them accurate conversion rates, which in turn enabled them to experiment with different marketing messages to see which ones resonated best with their potential customers.

When analyzing the data, they realized that a significant amount of foot traffic was happening around 11PM from people frequenting the local pubs. They also went to Google Trends to gain insight on the key food trends that were happening, which were chorizo and pulled pork. Utilizing these insights helped them implement a few small changes, and now 50% of the shop’s profits are being made from selling chorizo and pulled pork burgers, only one hour every night! For even more success, the shop is pulling in weather data for predicting needed inventory. More sunshine means more barbeques, and this data helps them be prepared. This clearly shows the transformative impact that results from capturing and deriving insights from data

The biggest takeaways from Bernard’s presentation were that businesses need more data diversity in the sources and types of data they’re collecting, consistent security and governance, and to build trust with their customers.

You can watch Bernard Marr’s full keynote, here:

Our next DataWorks Summit is right around the corner, taking place next month in San Jose from June 18-21st. Register today to catch all the keynote presentations, breakout sessions, networking events, and much more!

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