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The 3 Ways to Drive Business Outcomes With Data Analytics

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As a result, many organizations have all this information but only very limited ability to drive business outcomes using that data. There are several obvious and not-so-obvious reasons that organizations struggle with linking data analytics to business outcomes, and these problems aren’t just present in smaller companies. Quite the opposite actually — large corporations tend to have the hardest time drawing value from the massive amounts of data.

It’s common for organizational structure, corporate culture, company policies, shareholder values and problem-solving methods to get in the way of creating business outcomes from data. The increased number of C-level executives — all with different agendas, mind you — can hinder the success of using data to drive business outcomes.

Corporate cultures can make it difficult to implement change. So far, only the very best companies have been able to achieve organizational success through modern processes like end-to-end business planning. Even then, there are still gaps. Although business executives hope that purchasing analytics tools will result in corporate insight, that’s oftentimes not the end result. Furthermore, if poorly implemented, it these tools and processes cause more confusion than clarity.

To successfully leverage analytics for insight and improved business performance, organizations have to break down departmental barriers, create effective change management policies and … this is the hardest part … get people on board. Here are 6 ways that an organization can drive more business outcomes from data.

data analytics

Proven Ways to Put Your Data Analytics to Work

Start With a Business Problem

Defining a business problem may seem obvious, but it is a shock how many organizations skip over this step. Albert Einstein said, “If I were given one hour to save the planet, I would spend 59 minutes defining the problem and one minute resolving it.” This might sound extreme, but it does highlight the importance of clearly defining problems.

Unfortunately, most organizations purchase analytics tools, then try to find problems to solve. “That’s not how it works”, said Jeff McMillan, managing director at Credit Suisse, “You have a business issue and need to bring a set of capabilities to bear.” Organizations need to define problems first, then bring tools and software into the equation if they want to effectively drive business outcomes.

For example, assume Procter & Gamble has been trying to increase their sales by 10% for their Pampers brand. They need to define a clear problem such as, Huggies and Luvs are lowering their prices to make Pampers look expensive, thereby decreasing demand and ultimately sales.

Now Procter & Gamble knows that they need to find a way to increase demand, change pricing or other alternative solutions to solve their problem. This is the point where software and analytics tools come into play. Procter & Gamble could use prescriptive analytics to define and solve the problem at once, or they could run a series of what-if analysis and hope one of the scenarios produces a result.

Create the Right Organizational Structure

The structure of an organization establishes the various levels of communications, workflows, and the hierarchy of responsibility. The right structure produces powerful and positive results. An organization’s structure can influence the overall productivity and nothing is more true than the impact a proper structure can have on the ability to drive business outcomes with data.

There are four points of failure in an organization that create an inability to link data with business outcomes. If an organization wants to successfully drive business outcomes with data, then they need to address each four of these questions:

      What departmental barriers exist in our current structure? How does our current software and tools fit our structure? Who should conduct what data analysis? Where should the data team reside?

Breaking Down Departmental Barriers

Every department has their own objective and goals that often seem to work opposite of each other. For examples, sales and marketing or procurement and marketing department. The communication gaps between departments that need the data and the department/s that understands the data is often wider than Grand Canyon.

Organizations need to create a structure that closes this gap and creates an environment of collaboration between departments. Departments need to learn to shift their focus from “my department” to “our company”. They need to align themselves with the goals and resources of others in real time.

Start Small and Grow

One of my mentors said to me, “Once you start, you can never stop.” Granted, he was talking about shaving, but I think about his advice a lot. Too many organizations overinvest when it comes to analytical tools.

The problem is that buying sophisticated software and tools will require an organization to hire additional support that is specialized in running an organization’s chosen platform. Organizations need to be careful when they upgrade or purchase sophisticated tools, because you can almost never go back down.

Divide and Conquer

There is an on-going debate about whether more modern Business Intelligence and planning tools, while easier to use, come at the cost of customization and functionality. What’s our opinion on that? If you’re lacking either of those in one tool, whether it’s customization or multi-user type capabilities, it’s probably time to find something better.

It’s essential that planning tools allow executives and other “business users” to get answers from questions that have historically only been visible to analysts and modelers. By finding software with this new level of accessibility, business users are able to ask questions and visualize business outcomes without being dependent on the tech and math people.

Create Hybrid Data Teams

Organizations have different theories where the data team should reside — most believe it is part of IT. However, others believe the data team should be their own department or they should reside in the lines of business that own the data. We believe the data team has to be a hybrid, otherwise certain departments are alleniated.

Embrace and Manage Change Effectively

Ideal business outcomes are always changing. In this ever-evolving and highly competitive environment, organizations need to find a way to become flexible and utilize software tools to help embrace the change.

Business priorities, the market, customer demands and a shift in industry standards cause organizations to redefine business outcomes. For example, creating eco-friendly packaging is becoming a standard practice and customer expectation in many industries such as processed foods.

Organizations need to understand that purchasing software and analytics tools will not create company-wide adoption. If it was that easy, then every organization would have no problem connecting data with business outcomes. Organizations with the most success effectively manage change and are great at getting company wide buy-in. Employees and departments need to be shown the benefits of data in their own context.

Closing Remarks

Driving true, measurable business value with data is not easy — corporate structures, policies, and cultures get in the way, not to mention the many other barriers to change management. If an organization can start with a business problem, create a proper structure, and properly manage change, then they can be successful. Turning all of the “big data” — a word I’m sure we’re all tired of hearing — into real financial opportunities will be the differentiating factor among companies now and in years to come.

Editor’s Note: This post was originally published March 27th, 2016 and revised September 30th, 2018.

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