COVID-19 Is Prompting Enterprises to Adjust Integrated Data Strategies

The pandemic, with its various ripples across all aspects of our lives and society, has caught everyone off guard, prompting us to reevaluate our predictions of what the future holds. But out of the ashes, new systems and ways of working are already emerging.

The most obvious example has been the number of employees compelled to work from home, with evidence that such arrangements will become standardized post-crisis. Many brick-and-mortar businesses have also been forced to scale up their online operations due to the widespread disruption.

As for data-driven companies, changing consumer behavior means old strategies are no longer fit for purpose. The solution is to follow the data and create new models. To avoid confusion, forward-thinking business leaders need to make sure that enterprise data integration is a top priority.

Strategies related to data and analytics depend on both accurate information and a degree of predictability. And while the pandemic situation hasn’t affected the amount of data businesses collect, it has made the process of interpreting that data all the more difficult, given that the mindset of customers has undeniably changed. Even data harvested from internal operations is distinct from old patterns, reflecting an evolving situation characterized by shifting supply chains and leaner workforces.

In this milieu, many organizations are left wondering where they should be devoting their attention. One thing’s for sure – sticking to old habits while waiting for this whole thing to blow over won’t cut muster. Little wonder three-quarters of IT firms have increased spending on private and public cloud infrastructure services.

The Need for Integrated Data Strategies

Of course, it’s not just consumers who are behaving differently. The pandemic has forced organizations to address new regulatory requirements, too, particularly if they are serving the general public. Thus the increased demand for integrated data strategies encompasses all aspects of day-to-day business, with only the most responsive and resilient organizations likely to survive, let alone succeed.

By correctly interpreting and acting upon data collected, businesses can better respond to customer needs, restructure their operations accordingly, adapt to incoming regulations and take advantage of fresh revenue opportunities.

An ever-larger percentage of businesses are considered data-driven, with some form of analytics in place. The best and most simple thing many of these organizations can do in the current moment is to streamline their data. All too often, organizations feature departments that are siloed, using their own budgets and resources and building their own databases.

As such, while data is a watchword of all departments, the right hand rarely talks to the left. And without a unified approach, organizations lack agility and focus.

If the current crisis has taught us anything, it’s the value of acting quickly.

More Data, Better Decision-Making

Getting on top of data helps to inform companies’ decision-making, putting them in a better position to address uncertainties and reduce operational risk. But how can this be achieved in practical terms? Simply put, by streamlining data and managing it securely and effectively from central data hubs, dashboards and custom interactive apps.

The most useful tools are those that feature natural language querying and an intuitive UX that help bring non-technical users up to speed. Simplicity is key.

With a joined-up approach, organizations can make changes to planning, forecasting and modeling processes as situations develop and new data comes in. It’s about building a solid data pipeline that funnels information into a data integration solution, which then delivers actionable insights that leaders can use to inform strategy and drive value.

Something else that the pandemic has taught us is this: data is virtually worthless if organizations lack the ability to interpret it, the agility to act upon it, and the infrastructure to share it internally.

Data on the coronavirus itself has been accruing since the turn of the year, yet the way in which national governments have processed and reacted to it has resulted in wildly different outcomes.

In a business setting, Amazon, a major success story of 2020, underlined its status as a data-powered colossus by adjusting swiftly to the crisis with the aid of AI and machine learning.

Interestingly, the company’s algorithms are likely to get even smarter given the frenzied online activity of recent months.

Facilitating the integration of business information from multiple sources should no longer be seen as a task that organizations plan on getting around to when the time is right. With the volume of data generated continually increasing, the growing adoption of cloud computing, and data leaders under pressure to deliver solutions, doubling down on data and analytics has never been more vital.

6 thoughts on “COVID-19 Is Prompting Enterprises to Adjust Integrated Data Strategies”

  1. Considering two of the links appear to be related to SiSense, that suggests this may be an advertorial for them. I suppose it beats a Medium post…

  2. Maybe, I’ll grant, someone who has bought a range hood has a slightly higher chance of buying another than someone who has never bought one at all.

    But as a targeting method it’s clearly still at alpha version 0.0.3.

    But somehow it’s not just released to market, but making $billions.

    And I’ll never work out why, for some months, the advertisers were convinced that I was in the market for leg protecting pads for horses. I didn’t even know horses played cricket.

  3. “The pandemic, with its various ripples across all aspects of our lives and society, has caught everyone off guard”

    Yeah, like when I bough a 20 pack of N95 masks 9 months before the first outbreak and was contacting the SW Iowa county emergency preparedness planners for copies of their plans, and …

  4. Who wrote this Brian? Is it an advertisement? Did someone selling data integration services or software write it?

    If you don’t cite your sources and pass it off as your own work, it’s plagiarism. You are better than that.

  5. I like to search for things like yachts, vintage warbirds and other big ticket items regularly just to corrupt their advertising data profile on me. Eventually they’ll match it to actual purchases and realize what I’m doing, in the meantime how about a B-25 for less than $3 million?

  6. the trouble with data is the bias in the picking routine. Google knows I bought a range hood, now every ad is Range Hood. Before I needed it that might have been useful. Afterwards it is loss of advertising space.

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