Organizations understand the value of harvesting Big Data, but not everyone can afford a six-figure investment to get into the game.
Organizations understand the value of harvesting Big Data-but not everyone can afford a six-figure investment to get into the game. This is one reason why small and mid-sized companies competing with large enterprises have found great value in "predesigned" analytics that can get them going with their data right away.
Here is how the process works:
In certain industry verticals and/or specialty areas (like the supply chain), third party analytics providers that already have onboard expertise in mining Big Data and creating sets of "best practice" analytics make their analytics and reports available on their clouds. Once a small company ports its Big Data to the third party analytics provider for data mining and reporting, the company can call up any of the vendor's predesigned analytics reports to see how it is performing against key metrics for the industry it is in.
This data can tell a company how it is performing against internal goals, and it can also benchmark the company against a larger body of information that the third party has access to on the company's competitors. A service like this can jumpstart even the smallest of companies with Big Data harvesting and business analytics-for a little as $2,000/month in subscription charges.
Naturally, there are also some "cons" to this approach. Here is a list of six caveats that decision-makers in smaller companies should abide by if they engage a third party analytics service:#1-Sell the analytics service internally first, and then get going with it
There is the human tendency to get yourself onboard with a service before all of the key players in the business are firmly behind it. Resist this. Instead, IT should sit down with all of the stakeholders and map out the performance, market, customer and competitive metrics everyone wishes to see. If everyone knows what they expect before signing on with a third party, they are in a more informed position for making the right choice.#2-Avoid the "Top 20"reports "sand trap"
Too often, companies begin their analytics projects with good intentions, and even start circulating the new reports to managers. Then, when IT visits these managers it discovers that the same "top 20" reports that have been used for the past 15 years are still the major reports that managers rely on. This is not to say that some of these reports aren't valuable-but if you're not prepared to reevaluate how you're doing business and to take advantage of the new analytics you are getting, you are best off leaving third party analytics services alone.#3-Protect your intellectual capital
Most third party analytics providers allow their clients to develop their own customized reports on the cloud. In the contract, it will say that these reports are your "property"-but the ideas aren't. In fact, it is common practice for third party analytics providers to take the best practice ideas that they glean from their clients' custom work so they can incorporate these ideas into the baseline reports that they avail to all of their clients. If it is your desire to keep your ideas to yourself, you need to write that language into your contract.#4-Develop the next level of analytics expertise internally
Over time, companies will see how they can differentiate themselves over the competition with the strength of their business analytics and their ability to extract the essence out of Big Data. If you are a small company, you shouldn't make the mistake of assuming you are "done" with analytics as soon as you onboard with a third party provider. Instead, you should concurrently be looking to impart business analytics know-how into your internal staff so you can ultimately produce your own analytics. If you continue to rely on third party cloud services that deliver the same analytics reports to everyone, you won't gain any competitive advantage from your analytics.#5-Set up cross-functional business analytics teams
IT and end business users should be working together on business analytics and the use of Big Data. They need to decide how long Big Data should be kept-and they also need to continuously evaluate the queries they are posing to this Big Data, and where further refinement is required.#6-Never consider Big Data analytics as "done"
Analyzing Big Data is both an emerging and evolutionary process. As the specialty continues to grow, stakeholders in IT and the end business should have their ears firmly to the ground. You never know what analytics factors, technologies and best practices might be around the corner that can really make your business soar.