Perpetual Motion In Big Data Planning

According to a recent McKinsey report, "Big data: What’s your plan?" the authors note that although "The payoff from joining the big-data and advanced-analytics management revolution is no longer in doubt," most companies don't have a plan for what to do with that data.

Do you know what you need to map out your own blueprint?

McKinsey calls for creating a plan that includes three core elements: a game plan for assembling and interlinking data inputs, analytic models for solving broader optimization problems across functions and business units, and intuitive decision support tools that integrate data into day-to-day processes and translate modeling outputs into tangible business actions.

But the beauty of McKinsey’s insights lies not in simply listing what you need to get started, but instead in highlighting the challenges that could get in the way of making a plan work.

The roadblocks are listed as establishing investment priorities, balancing speed and cost, and ensuring acceptance by the front line. But as with so many challenges, they can be made easier to overcome by reframing them.



Where are you now?

McKinsey says that as companies develop Big Data plans, matching investment priorities with business strategy calls for making difficult decisions about what data architecture, models and tools that organizations should bet their budgets on.

Solve this challenge by first understanding that you can't begin matching investments to business strategy until you have mapped your needs. It's premature, for instance, to begin discussing what kind of data warehousing system you need to invest in before you have a clear picture of your organization’s expectations of -- and commitment to -- your analytics infrastructure and initiatives.

From your objectives, scope and resources to your methodology, tools and management, you have to understand whether your organization is engaged and bought into the activities required for the success of your business long before planning investments.

Is your strategy agile enough?

McKinsey recognizes that executives are struggling to balance the need for affordability and the ability to shift quickly into action mode with business realities.

"Once some investment priorities are established," the report notes, "it’s not hard to find software and analytics vendors who have developed applications and algorithmic models to address them."

But before rushing to purchase the technology, it's worth stopping to consider whether the organization has the people and processes in place to actually use the technologyover the long term.

Cost is always a consideration and making progress is critical but incremental gains  from pairing people and process with the appropriate technologies will still bring benefits to an organization -- and the extended timeline will give you the breathing room to prepare for responding to consumers' quick behavioral changes.

Often, the most important decision you will make is not between the cheapest or the fastest technology solution but about which tech partner will enable your team and your organization to activate the next step in your data maturity plan.

Engaging organization-wide stakeholders

Lastly, McKinsey tackles the issue on everyone's mind: Once a program is in place, how do you engage the organization?

McKinsey details several methods for easing implementation by linking easy-to-use decision-support tools to processes that enable internal stakeholders to apply their own experience and judgment to the outputs of models.

Obvious, but left unsaid, is that the organization's business objectives lie at the very heart of any program designed to engage an organization with a new data strategy. Whether you're talking about training employees on how to speed data-gathering activities or enabling them to take action on data-driven insights, adoption efforts will be strengthened as they continue to drive the business forward against its goals and strategic objectives.

Once stakeholders can understand a shared vision of how a data and analytics plan can draw existing and new customers ever closer, these challenges can morph into a closed circuit of opportunity. A clear view of how you want consumers to engage with your offerings and react to your brand can inform your business strategy, evolve the technologies that will help drive it and encourage the buy-in to make the most of it all.


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