Technology has constantly been available to humans in abundance through various conformations, but the realization and usage of it have gained expeditious momentum lately.
Three mainstream technologies that are working towards propelling the globe’s immediate future are the realities — virtual, augmented, and mixed (VR/AR/MR) — artificial intelligence, and cybersecurity. The “only” domain that can pierce into these technologies are analytics and business intelligence (BI), principally owing to the diverse outcomes they can churn out of these technologies. While many might contend with the “only” aspect, sensing application development and maintenance (ADM) is a close second that has equal or possibly stronger potential to introduce sizable interventions.
Having said that, the firms that enable AR/VR/MR, AI, and cybersecurity are already customizing their products, layering application enhancements, and conferring support to suit the demands of their customers. By understanding this very premise, the somewhat convoluted definition of ADM doing the rounds can gain more girth on the scale of clarity. Concisely, it becomes simple to explicate the actual value-adds.
Now, let’s take a look at how analytics solutions and BI are the extra muscle that businesses could cling to align strategies and rake in more moolah. The industry that has always been in vogue is the media and entertainment (M&E) industry. Now, supervening analytics and BI into it can spin off rewarding reactions across tangents. The new age domain combined with the ever-shining “superstar” industry can be the ultimate “vendor’s mascot” and the “client’s jackpot”, when it comes to availing or conceding information intelligence and visualization service provisions.
Therefore, the choice remains critical. Such solid “vendor’s mascots” imbibe decision-making in their outcomes, impart statistical modeling, algorithmic processing, and rich dashboarding methodologies that can cater to select known or unknown situations without compromising on a client organization’s fundamental objective and, in that, evolve and alter course to proliferate overall business returns.
Moving on, an industry like M&E, which has a great fan following, does very little to utilize the cogency of analytics and BI. Approximately, only 20% of the M&E companies today are either subscribing or seriously considering subscribing to analytics and BI solutions. Companies in both these extremes need to be made aware of the positives of preparing them for a vibrant analytics and BI environment.
The M&E industry is estimated to produce a revenue upwards of $85 billion in 2017 and reach about $115 billion by 2020. However, many renowned international M&E companies have shut shops due to their reluctance to adapt to advances like digitization. In scenarios like these, digital analytics techniques could be very telling and direct companies on the right path. Analytics and BI can be a palpable game changer given the current dynamics and circumstances of the quickly changing media world.
The average lifespan of any consumable output, product, service, template design, or idea across the M&E sector is not beyond 2 to 3 years in this contemporary market. There could be repetition in multiple flavors but in the full throttle, innovation-prone M&E industry, how long can you rely on marginal improvements, “loyal fans”, and recurring ideas? “Loyal fans” will continue to stick if the companies are consistent with generating appealing content and topics of interest. An upgrade to the above elements, even if it experiences a marginal delay, can cause immediate repercussions and conceivably jitter their go-to-market game plan.
Picture these few possibilities. A high-budget animation movie is to be made. The production house would still prefer to work out the most optimal expense methodology. There might be animations and other items from previous in-house creations, which could be reused or moderately touched to fit the bill. How is this possible?
A term called “productivity improvement analytics” is the answer. Empowered with the nuances of probabilistic modeling, productivity improvement analytics could be conducted to absorb the media house’s data, analyze it, and equip them with the right information about reusable components along with the percentage of reusability. As a result, revenue spillage, rebuilding existing animations (characters, backdrops, etc.), employee boredom, and productivity inefficiency can be averted.
In the absence of in-house data, current trends coupled with assumptions in the select industry (M&E in our case) could be used as data to come up with inferences and recommendations.
Plying analytics and BI into the veins of publishing, another important belt under the M&E scheme of things, sets the platform for another classic case of data’s vitality. With increasing number of news and journals being consumed digitally, web analytics remains material for publishers. The entire gamut of publishing might get rejigged by publishers being well informed about their three selling points:
- what’s going to be read more/what is being read more?
- where to place an article or news depending on the content?
- how to scale up readership?
At this juncture, it must be noted that analytics and BI can be applied to the print facet of publishing as well. A merger between machine language, analytics, and BI in the recent times has been powerful and zealous in ways that it can detect human sentiments to propose solutions. What if this adoption is used to solve for on-the-fly movie reviews? Ingesting neuro-linguistic analytics into the filmmaking process can help predict the reactions of audiences when they watch a movie on the big screen post-release. Using neural science and analytics, directors and production houses can course correct the scenes as they are shooting and, based on the prediction, release a more quality box-office savvy version for the audience.
Drawing a close, the customer could be the King, but the underlying data, triggering analytics, and business intelligence drive the King. So, what’s your decision?
N.B.: If you’re looking to make a choice, even then analytics and business intelligence can help you make one!
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