Supporting cross-functional
data collaboration

woman supporting cross-functional data collaboration

These are strange times, but through the uncertainty, we’re finding new and different ways to work together. Those who are able to work from home are now relying solely on virtual communication and interaction. It has quickly become the new normal, and for those people who have traditionally relied on in-person interactions to get things done, agility is a necessity. When professional proximity is replaced by social distancing, there’s one indispensable weapon: effective collaboration. 

Why does collaboration matter?

The concept is so ingrained that it’s almost a cliché — after all, who would argue against collaboration? In the most common sense, it means working with other individuals to complete particular tasks. In a professional context, it requires pooling individual skills, group time and company resources within a business environment to launch and execute initiatives that benefit the brand and boost the bottom line. It sounds so easy, and so fundamental. 

However, in the real world, it can be like chasing the Loch Ness monster. Separate departments and functions invariably have their own priorities, which often differ and sometimes conflict. Some resources are siloed by design, others through benign neglect. Individual idiosyncrasies and traditional boundaries are hard to overcome, while instinct and anecdote make poor substitutes for research and analytics. The list of possible bad outcomes is long: close colleagues don’t work off the same page, routine practices fall afoul of compliance mandates, and different constituencies pursue different targets. This happens in ordinary times; during a crisis, it’s even harder to achieve. 

People and data working together

Moving ahead, one side effect of the current environment deserves attention. People and data are the two most important resources within a modern enterprise, and they are now similarly dispersed. Of course, this feature also shows us the path ahead — data-driven intelligence to guide business-wide collaboration, regardless of where the people or the data currently reside. 

Remember, technology solutions are always critical, but technology is only part of the solution. Databases, private and public clouds, performance and scalability are all vital, but intelligence is a human attribute. That makes Data Intelligence a people-and-process issue. During times of crisis, our top priority is to make it easier for people to find the data they need, trust it, use it, enhance it and share it.

So how is this manifested in the current climate — and how will it continue offering benefits when the crisis passes?

Consider the problem cited above with regard to working off the same page — why does this hinder collaboration?  Because within the business lexicon, there’s always room for multiple definitions and semantic confusion over simple terms. Many data analysis initiatives fall short because there are differing definitions of, for example, ‘customer value.’ None of those meanings might be wrong, just different enough to mess up the analytics. To muddy the waters even more, organizations often lack a simple platform where all employees can access the same data and collaborate easily.

Improve cross-functional data collaboration

This is where a glossary can help to eliminate all sources of confusion. A true business glossary ensures that each business term is identified with a single name, definition, value set, source of business rules, authoritative source and accountable party. Even with disparate users and formats, it keeps out additional interpretations.

With that common language as a baseline, let’s go further. For data to drive collaboration, it must be collated, relevant and easily searchable. The best way to do that is to build and implement a comprehensive catalog. 

A data catalog offers full visibility into all relevant data with rich context. It lays out who created it and why, who added to it, who now owns it, etc. More than just scan existing metadata, a good catalog creates its own, making it easier for the next set of users to find what they’re looking for. With optimal organization and agreed-upon definitions (remember the glossary), it empowers a new generation of data citizens to access the trusted data they need, without waiting in line for help from data science or IT. 

One last example: While colleagues and resources may be kept at a distance, the fear of non-compliance is always close at hand — there are no exemptions for crisis conditions or a remote workforce. That’s why it’s important to establish Lineage — mapping relationships between diverse data points to maintain transparency of data movement, and visualize how particular data sets are built, aggregated, sourced and used. This enables collaboration without violating the myriad mandates that now define every business environment. 

In sum, let’s acknowledge that these extraordinary times will have a long-lasting effect — many of us may not be returning to the office for a while. Having a centralized tool to access data and collaborate on projects is more important than ever because data is highly needed, and when you can’t do in-person meetings, a centralized platform gives teams an opportunity to leverage for this necessary collaboration.

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