We’re not seeing the results we thought we would. What did we miss?

The amount of information and analytics organizations have access to today compared to years ago has increased exponentially. This deluge of data and information has created challenges and opportunities for CEOs who are accountable for the potential and actual achievements of analytics.

A report from McKinsey & Associates noted:

Too often, the enthusiastic inclination is to apply analytics tools and methods like wallpaper—as something that hopefully will benefit every corner of the organization to which it is applied. But such imprecision leads only to large-scale waste, slower results (if any), and less confidence, from shareholders and employees alike, that analytics initiatives can add value. So you are not alone in not seeing the desired results from analytics. However, companies successfully adopting data-driven programs are doing these things.

Merging Technical Capabilities With Business Goals

Companies that successfully adapt to advanced analytics understand that the best input solutions appear when data scientists and executives work together. These organizations fuse their technology capacity with their core business objectives.

You get a gap in results when businesses centralize their information or store it in badly coordinated silos. Neither method is efficient. Too much centralization creates bottlenecks and prevents buy-in. The decentralized route can lead to a disconnect between varying models. These approaches will lead your data scientists to think they are not adding value to the company and drive down adoption and confidence among stakeholders.

Combining talent from the data science side and the business side will give your business the capabilities it needs to extract insight from your analytics.

Cultivating a Clear Vision of Purpose For Advanced-Analytics Initiatives

Most organizations struggle to adopt advanced analytics programs because of a lack of clarity on how to execute against big data concepts and applications. These companies fail to define significant problems and invest in cultivating the right skills. As a result, adoption slows or completely stops.

However, with the help of data scientists, the whole company can gain a clear vision of your business intelligence programs. The person leading the program can set up educational meetings to teach the fundamentals of advanced analytics. These meetings could dispel misconceptions and serve as a foundation of understanding of the analytics function throughout the organization. This educational approach will create the management capabilities required to lead and direct all analysis toward purposeful action.

How the Right Analytics Talent Can Get the Desired Results

Analytics talent is like a mosaic of skills and responsibilities. Of course, various abilities and functions might merge depending on the task at hand. However, defining each role is essential in ensuring you hire quality vetted analytic professionals. Having quality vetted professionals on your team will help you answer vital questions like:

• What was the cause of the problem?
• Why did it happen?
• What will happen in the future?
• What is the best way forward?

With the right data team in place, you gain a more unobstructed view of your operations and logistics. You can see which parts of your organization are working efficiently or inefficiently. When you discover gaps in results, your team of business intelligence professionals can quickly fix it.

Chisel Analytics can find the right data science talent to help you get your desired outcomes from advanced analytics. Chisel vets top talent with our proprietary skill assessments across 6 key elements to ensure you hire the most qualified analyst for your critical needs – from project based needs to full time roles. We ensure that the addition is seamless, giving your company the efficiency and reliability you need from your workforce.