Making The Most of Corporate Data with A Strategy

2014-1015 - Corporate Data Strategy

Making The Most of Corporate Data with A Strategy

Over the past few years countless thousands of companies in the US have taken the leap into the new data revolution. Due to weak data strategy, that leap has unfortunately left behind many failed efforts or those that just did not live up to expectations. Getting the most of your data is not as simple as purchasing a business intelligence analytics platform and plugging it in. It requires planning well ahead of the purchase, along with ensuring adoption amongst key employees and departments. In this post I outline a few areas that, given the right attention, will help you reap rewards from your analytics efforts.

Define the goals and outcomes for analytics
Without clear goals and outcomes most analytics projects are doomed from the start. For CorSource, potential customers often first come to us expressing that they need a software solution to analyze their data. While this eventually could become the end result, stepping back from a specific solution is the best way to inform the final technology decision.

How do you wish to use the data? To profile customers, to increase sales, to monitor inventory across systems, to optimize your finances? There are many ways companies can take advantage of data harvesting – it’s a matter of finding what is likely give you the biggest initial ROI.

Who will use the analytics from the data? Define the area of your company that will get the most out of analytics and start there. This area becomes your shining example of why analytics could be advantageous for the entire company. These employees become your champions.

Is your data sound? Profile your data and understand whether or not you have any data quality challenges. As the saying goes, bad data in, bad data out. By doing this before deployment, users  know they can trust the data they are using to make important decisions.

Do you have buy-in from leadership and other stakeholders? From the start, leadership and other stakeholders need to support the idea of the organizational culture shift to being data-driven. Without this, adoption will be slow, and overcoming any hurdles in the implementation process will be very challenging.

Start researching platforms
There are tons of business intelligence platforms out there. It’s important to have knowledge of the leading platforms, but more important is finding the right one that fits with your company goals.

Do you need something full featured or more simple? A cloud-based Business Intelligence platform will give you the most versatility when it comes to connecting multiple systems. These are appropriate when non-analyst staff will be accessing analytics dashboards and reports. A Data Discovery tool is great for analysts who only need to do occasional one-off analysis. Data Discovery does not equal Business Intelligence. Other forms of Business Intelligence include Predictive Analytics and Prescriptive Analytics.

Is the platform provider ranked highly with an analyst firm? While analyst reports, like those from Gartner, aren’t “the be-all and end-all”, they do provide a starting point of seeing which software vendors to consider and avoid. These in depth reports will help you understand the features, positives and negatives of leading vendors.

Does the licensing model fit your company’s needs? Some software is licensed on a per user basis, while others are licensed with a flat fee for unlimited users. Depending on your ultimate goals one model or the other could make the most sense. It’s definitely one of the factors that you should weigh.

Does the platform meet your business and technical requirements? Selecting the best technology should be driven by the business side of the company, but needs to include the IT side as well. Your tech team can uncover any kinds of technical infrastructure hurdles that could exist with different platforms, and in some cases will demonstrate why one tool would be too large a burden, or at least help to determine the actual cost after one adds in the technical work.

Plan your implementation
The biggest reason new technology fails is that adoption rates amongst users is too slow or too low. Too slow means that there are not enough “satisfied customers” to demonstrate its success. “Slow” often results in low adoption rates as motivation and momentum wane. The key is finding the best way to implement rapidly and making sure that people know how to use the new tool and get value from it for themselves and the company. With Business Intelligence, reports that previously took days to complete can now be done at the click of a button – this helps “sell” the idea of an analytics platform for all. As do a couple of simple dashboards that provide real value to select employees, particularly decision makers at the top of the organization.

Are you going to do this in-house, work with the platform provider, or get assistance from a third-party service provider? There are many ways to implement the technology, and who will do it depends on the experience of the team and the complexity of the technology. Most modern analytics platforms can be deployed in weeks, rather than the months required by legacy tools. Typically, some kid of assistance is needed from the software vendor or third-party.

Who is going to train employees? Training employees to use a new tool is of course essential. With BI some employees, like analysts, will need to understand the backend basics to create reports for company staff. Eventually, with help from an expert, they can learn how to also create dashboards. The end users simply need to be shown how to access the tool and how to use the information.

How is the company going to become data-driven? Developing a data-driven culture is not easy, but it’s essential to competing today. At least on a basic level, employees need to be taught how to look at data, comprehend it, analyze it and act. And then repeat. It needs to become a daily habit and part of the regular workflow. Spreadsheets and antiquated systems need to be put on the shelf. Leadership must drive their communications to employees with data and data analysis to demonstrate that they are committed as well to a data-driven organization.

Continue to monitor, improve and expand
After the platform is deployed, the company should monitor usage and success in meeting the initial goals. Likely, in the first few months there will be tweaks to the interface and many new reports and dashboards as people discover its value. After a number of employees have success with BI and the system is optimized, it’s time to start planning Phase 2 and then expand further into the business.

I hope this gives you a good overview of what to expect and how to approach your analytics initiative. Feel free to reach out to us any time with your questions about Business Intelligence implementation strategy.

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