Bring Data to the Center to Unlock Innovation

Connected intelligence
Fact

The longest-tenured companies on BCG’s most innovative companies list use platforms to gain access to different capabilities and sources of data, which they then use to build new business models or develop new products and services. (Source)

The future of business will be fueled by data – driving nearly all decisions in real-time. Today’s technology juggernauts have achieved their success by letting data flow freely within their organization. It’s time you put data at the center of your organization to unlock its full innovation potential.

Data Fuels Connected Value

According to BCG, 80% of the most innovative companies utilize data to drive advantages in their organization and industry. Companies like Philips, Nike and Google continue to invest in their data strategies, letting data flow freely throughout their organization to improve their product offerings and to reap rewards in terms of customer insights, building new capabilities, and business model innovation. However, most companies continue to be application-centric when developing new products or service offerings, sticking to a specific use case in which each application has its own database and is responsible for collecting and storing the data it needs.

Putting data at the center means that data is the primary driver of value in your products, experiences, marketing tactics, operations – your entire company. Data and the insights generated from it is often more valuable than a company’s core product or applications alone, furthermore, data-centered strategies can create significantly higher gross margins and revenue efficiency.

Fully unlocking the value of data often requires rethinking your overall offerings and business model with data and the ability to leverage it as a core advantage.

A great example of data being the primary driver from the beginning and starting with the question of “How and why should we leverage the data we produce?” is Propeller Health. They have reinvented how over 80,000 people manage their chronic respiratory illnesses by embedding a sensor in inhalers to collect real-time data on when and how often people use their medication. By integrating usage data with external data like weather and air quality, Propeller is able to provide a real-time, personalized treatment plan. Many people using Propeller have seen fewer symptoms, flare ups, and unplanned asthma attacks after one month – leaving the potential to save billions in health care costs.

Source: Propeller Health

Exponential Growth of Data is Disrupting All Industries

To most, the field of data analytics is not new, but it’s becoming more important than ever to understand as part of your organization’s overall strategy. From applications and internet connected services, to internal systems and employees, data is being generated in extraordinary quantities. The issue is that many organizations face is that they are unable to fully make sense of this data fast enough before it loses its value. Data is in-fact perishable. Its value is time-sensitive and has a limited shelf life.

According to IDC, every person online will create 1.7 megabytes of new data every second by 2020. Furthermore, the world overall uses 4,416,720 gigabytes of internet data per minute.  At this rate, the concept of ‘perishable data’ is more relevant than ever. Businesses need to prepare themselves in order to translate captured data into actionable insights as fast as they can.

As a brand, you’re probably swimming in an ocean of customer data, but are you a data-centric company, or are you actually just a company that has a lot of data? While every department knows that data is critical to the business, few have plans in place that make the most of it.

A great example of a brand pivoting to better utilize their data came in 2008 when Nike decided to shift to a data-driven marketing strategy called “category offense” to better segment their customers. Rather than segment their audience by geography, they started segmenting the athletes they serve by the sports they play.  The thinking behind this is that soccer players have more in common with each other than people who simply live near one another. As a result of transitioning to a data-centric strategy, Nike’s sales rose more than 70% over the next 7 years.

Source: Forbes
Activating Data is a Huge Challenge.

Similar to Nike before their shift, many organizations are losing valuable insights as there are many disjointed sources generating and collecting data on their own, contributing to only bits and pieces of the big picture instead of rendering a broad view and the benefits that come along with it.

Four Categories of Data-Driven Benefits

The benefits of connected innovation come from producing four categories of “intelligent” deliverables as shown below, each built on top of one another, and in order of increasing complexity and sophistication. This approach is part foundational and part innovation, like a balanced portfolio.

Actionable insights, optimization, augmentation, and automation
Definitions

1. Descriptive analytics: Generating insights and identifying patterns and trends from historic data

2. Predictive analytics: Building models to make predictions that drive better decision-making and improve outcomes

3. Prescriptive analytics: Maximizing outcomes and making automated recommendations and decisions

1. Actionable insights
Starting with actionable insights, data-centric solutions can be used to drive deep actionable insights, which can be surfaced in mobile, desktop, or other user experiences. This allows real-time actionable intelligence to be delivered to business operations.This level of intelligent data is similar to traditional business intelligence and descriptive analytics, and is built from development of key metrics, aggregations, statistical analysis, and informative data visualizations.

2. Optimization
After actionable insights, data can be used to optimize realization of company goals and impact. This is possible by leveraging machine learning and artificial intelligence techniques for predictive and prescriptive analytics purposes, e.g., predictive models, targeting, personalization, and recommendations. This level is able to generate a deeper understanding of the data than what humans are able to discover on their own. It also usually generates exponentially more value than traditional BI, statistical, and data visualization-driven insights.

3. Augmentation
With a foundation established for generating insights and optimizing business outcomes, augmentation is the next step. Augmentation, a.k.a., human augmented intelligence is an application of AI to automating tedious, boring, and repetitive tasks that people need to do in their daily work. By automating these tasks, workers are able to focus on increased value-add tasks, productivity, creativity, and overall work enjoyment. It also enables companies to be able to do more, both faster and more intelligently.

4. Automation
Finally, AI-based automation is a complete automation of critical processes or tasks that were previously done by humans. Collectively we refer to this four tiered approach to value generation as ‘Applied AI.’

Build Your Data Foundation

Companies that invest in data-centricity can drive messaging, efficiency, and superior customer experiences across all functions, not just in marketing. The ability to turn data into value requires building a data foundation that includes the following components:
  • Data source identification
  • Data ingestion, integration, preparation (ETL, cleaning, processing), and analytics-optimized storage
  • Data access and querying
With an established connected data foundation, we can start to unlock deep actionable insights and intelligent solutions to drive better decision making, predictive and prescriptive analytics, augmentation, and automation
 
With an effective data foundation in place, the data generated by connected systems can be applied to drive real value. Rocket Wagon help’s customers with a crawl, walk, run approach to creating intelligent connected solutions.
 
Our recommended approach is as shown.
Build a connected data foundation then generate actionable insights then understand cause and effect then applied AI and data science.

Building your connected data foundation unlocks many opportunities to drive real business value. This starts with the ability to generate deep, actionable insights. We then help companies focus on cause and effect through experimentation and causal inference strategies. From there we leverage AI, machine learning, and data science to enable advanced use of data to drive bigger results.

A Connected Data Strategy and Expert Team For The Win

Ultimately, most companies pursue incremental improvements to existing technologies, while often failing to realize the full value and potential of the data they own. This is especially true of emerging digital and IoT connected products built without a data strategy in mind. Every product, whether digital or cyber-physical, should be built to leverage the data they collect in a way that maximizes impact, revenue efficiency, differentiation and competitive advantage. 

Becoming a data-centric company and realizing the high efficiency revenues that come along with it requires adopting an agile approach to developing and executing a data strategy. As we said above, this starts with building an intelligent connected data foundation that can power deep actionable insights and advanced analytics. A data foundation is not the only ingredient for data success. You also need an expert team of machine learning engineers and data scientists, both of which are in very short supply. This expert team is able to drive real differentiation and competitive advantage when combined with the right data foundation, processes, and a wide range of domain experience and expertise. Experts in applied AI also help choose the right tools, approaches, and mitigate risks. 

The complexity and amount of effort to get to this desired state is not lost on us. Gathering insights out of data after all is a science, and science takes time!  A successful data strategy needs to be driven by executives who understand the process and who are focused on the end result where the true value lies – transforming business data into assets that help organizations improve revenue, reduce costs, seize business opportunities, improve customer experience, and more.

Once you’re there, the time and team expenditures can easily be justified as your data strategy connects you to opportunities that form your business’ future.

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