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What does it mean to be data driven in 2020?

04 Nov 2020
In the past 10 years, many companies have set themselves a new, ambitious goal: to become data driven. Some want to realize digital transformation, others aim to seize the opportunities presented by Artificial Intelligence (AI).

Yet a survey conducted by NewVantage Partners earlier this year shows that most firms struggle to achieve this goal.

Time to have a closer look at data-oriented goals. In this blog, I'll share what we believe 'being data driven' should entail today.

What's happened in the past 10 years?

Businesses have used data for quite a while, and becoming data driven has been on managers' agendas for a long time. Here's an example: there's a Harvard Business Review book on the topic that was published in 2008 but is still relevant today, especially when discussing companies' struggle to manage data as a strategic asset.

At the same time, a lot has changed since then. We have definitely achieved something in the past decade:

  • Most companies create standard (data) reports on a daily, weekly, or monthly basis to review performances and make informed (fact-based) decisions to steer the business.
  • Excellent self-service business reporting tools have been developed, which generate reports for all kinds of business review processes (examples include QlikView, Tableau & PowerBI).
  • Leading companies have decentralized the use of data by enabling employees across the organization to analyze raw data and independently create insights.

However, the latest technological developments open up a world of opportunities to data-driven companies: they can now truly redesign their business using data. In my view, that's what being data driven should be about today.

Data-driven operations: 3 new paradigms

1. What if your assets or machines could intercommunicate, and you could receive live status updates?

The latest technologies — especially the Internet of Things — can connect all kinds of assets and machines to the internet, so they can share information in real time. This offers exciting opportunities to radically change the way in which you run your business. Here are two examples:

  • Smart waste containers

In Rotterdam, waste containers have sensors that measure a container's filling level. Garbage truck routes are no longer fixed: they are determined based on filling rates, which means cost and performance are optimized.

  • Predictive maintenance

ProRail currently runs a pilot to monitor the condition of the railway network using sensors (vibration) on passenger trains. Until now, they've used a dedicated inspection train that doesn't measure tracks every day and is more expensive. So, ProRail is taking things up a notch.

2. What if the stakeholders in your ecosystem could easily share data, and you could use data from other actors in your decision-making processes?

As we move towards cloud computing and increase our use of APIs, it gets easier to share information. Here are two examples:

  • Port of Rotterdam

In the Port of Rotterdam, network collaboration creates a win-win situation for all parties involved. You can read all about it in our blog 'Increase your capacity by going digital: how does the smartest port in Europe go about it?

  • Schiphol Airport

Five independent parties handle cargo at Schiphol Airport. To ensure effective operations, they require accurate arrival information on aircraft (time and gate). Schedule changes used to be communicated by phone, creating delays and inefficiencies. Currently, Schiphol shares the latest aircraft information with its operational partners in an automated way via Operational Flight API, allowing them to improve performance.

3. What if advanced optimization or data science models are available to your company, and you could use them to optimize decision-making?

Machine learning and optimization models are becoming more widely available. This means large amounts of data can now be used to drive business decisions — which is impossible when you process them manually (in Excel). Here are two common use cases:

  • Artificial Intelligence

Demand forecasting, price optimization, and virtual assistants are three ways in which you can use AI to improve business performance. They represent the tip of the iceberg: the opportunities are virtually endless.

  • Integrated operational planning

Most companies have separate schedules for their operational processes, which results in a suboptimal overall plan (examples include manufacturing processes in a factory or passenger processes in a(n) (airport) terminal). Aligning the individual schedules could yield significant benefits.

Briefly put, there's a myriad of possibilities, but companies struggle to implement solutions. Want to know more about the challenges they face? Keep an eye on our next blog posts!

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