This article was originally published in eWeek.
DataOps is to industrial transformation what yeast is to bread. Your digital efforts will likely fail to rise throughout the organization without it.
In recent years, DataOps has emerged as a discipline to describe tools, processes, and the right organizational structure to support a data-focused enterprise. While Google presents a plethora of different definitions for the practice itself, one thing cuts across them all: the importance of collaboration to succeed.
DataOps is not a product for purchase today. It is a practice-based on people, processes and technology that is currently rising across industrial operations. It’s a tool that will ultimately lead to the establishment of a new product category – a data product.
According to Forrester, a data product is a component that ingests and delivers data used by an insight solution for decisions and actions. This is the goal – empowering companies to use contextualized data in their operations to create value. That is the reason that DataOps exists.
Getting to that point is not easy. DataOps was initially thought of as a PR ploy or a risky financial move – yielding no real return, only debt. But today, we see many industrial operations awakening to its value, realizing that data, when liberated and contextualized, can serve as a company’s foundation for sustainable transformation – if they figure out how to use it right.
Advanced data operations are what will drive your transformation
Most organizations today struggle to transform due to lack of know-how, technology, and tools to do the work. There’s no shortage of data in most cases, but there’s a general lack of understanding on how to extract it, bring it together and use it in an actionable way.
We’ve learned over the past few years that this fear and misunderstanding of data will only delay your transformation. The idea behind DataOps is to get teams over this hurdle, by bringing together both data and domain experts, to work in tandem, to uncover the value of the data.
One of the main roadblocks to becoming a DataOps-driven organization is a lack of digital maturity. A digitally immature company typically expects short-term gain from narrowly focused digital efforts, rather than thinking about the long-term goal. These companies are not able to scale solutions, and thus the value of data is stunted early on.
Digital maturity comes when you have brought purpose and strategy to your data operations; you have built the right mindset among your people; and you have established a way to capture value from the data across your entire company and even value chain.
Clear pitfalls for the digitally immature
It happens all the time. Companies with good intentions fail to adopt a strategy to become data-centric, in the face of a few internal hurdles. One of the most common hurdles is the well-established silos that are difficult to break.
For DataOps to succeed as a widely embraced practice in your company, scaling alone is not an option. However, collaboration between departments is essential, along with a strong mentality that everyone is a data consumer.
The idea of waiting to reap the rewards of DataOps can also be a difficult pill to swallow, especially for boards that want to see quick ROI and steady shareholder return. But digital processes are not overnight rainmakers, and if a short-term approach is applied, your initiative to become a DataOps org will likely be killed, which in the long run means that you will eventually be surpassed by competitors who managed to make it work.
Three steps to bringing DataOps into your organization
The challenge is great, but the opportunities are even greater when it comes to industrial DataOps. IDC predicts that by 2023, 60 percent of organizations will have begun implementing DataOps programs to reduce data and analytics error by 80 percent.
That’s a tangible outcome, and one that is possible once you’ve successfully introduced a new way of managing data across the company – dealing with data diversity and collaborating with others to extract more value. Three things are needed to truly make that happen.
1. Make industrial data available.
Your data is probably locked in someone’s silo, and it’s time to get it out. Industrial DataOps can help you with data convergence, getting you going on the integration process when bringing together the data from multiple sources across the company – fusing them so that it’s available to all, in one place.
2. Make data useful.
Once the data is integrated, it must be contextualized and made available to people in a secure way. And all consumers need to be able to access it and use it in an easy way, to help them understand its value and how to act on it.
3. Make data valuable.
A DataOps-driven organization will apply advanced data models that lead to important insights for the company, which can then influence decision-making and guide people toward actions that will produce the greatest return in the end.
DataOps is the gift that keeps on giving
Getting your organization to the point where data becomes a new product category will take time, people, and dedicated efforts to weave the DataOps mindset across all corners of the company. Everyone must be on board, and the data must be presented in a more human way so that all users are empowered to act on it.
Just as you would with the raw bread dough, nurture it to rise throughout your company so that eventually it can be consumed by all. Time will show that your commitment to becoming a data-driven organization will be essential to your digital transformation. It’s do or die in the industrial DataOps world.
Vice President of Product Marketing: Petteri’s professional career spans across enterprise SaaS technologies, where he has found himself at the intersection of emerging transformational technology development and its commercial applications for customers. Prior to Cognite, Petteri worked in senior product management, marketing, sales, and general management positions for companies such as at Sumea, Rovio, and Cxense. Petteri has a master’s degree in technology from Aalto University in Helsinki.