Rapidly Advancing Technology is Fueling Intelligent Enterprises but requires a Fundamental Shift in Leadership, According to Accenture Technology Vison 2018
The annual Accenture Technology Vision 2018 has been released with insights on some of the key technological trends set to disrupt the business world over the coming years. The first such disruption is Citizen AI (Artificial Intelligence) where AI will move beyond its geek-sphere to impact everyday business solutions. The next one is Extended Reality which includes both Virtual and Augmented forms are helping work by reducing distance between people, experiences and information. While business analytics is playing a major role in decision making, organizations ought to be concerned about the legitimacy of certain data sources. Thus, data warehousing and its veracity will be another hot topic so that the rights insights may be gleaned out. Another challenge will be connecting intelligent enterprises, which legacy systems are often unable to tackle. Businesses are also spending on robotics and immersive experiences using intelligent distributed systems.
Uploaded Date:23 February 2018
Reading List: Applying Analytics
A recent report released by the MIT Sloan Management Review analyzes the role of analytics for innovation in businesses. Every conceivable business today is being aided by analytics to a large extent. This includes medical care, sports and startup funding. Industry giants such as Netflix and Disney are making use of business analytics to free up their operations. Yet, there are mistakes galore from the algorithms. The human side of analytics is being ignored. The right kind of data needs to be extracted from the huge pile of often meaningless data. It is the human brain which can extract information out of the enormous raw data. Once biases are removed, talent recruitment can be executed very well using the right kind of data.
Uploaded Date :19 February 2018
Data and Technology don’t change your Culture, they Reveal It
Contrary to popular opinion, data-infused business analytics does not always get things right. In fact, a common fallacy called “black box” can occur, which leads to the algorithm making a decision with little transparency or accountability. One company that has bucked this trend in Cava Grill, which is a restaurant for Mediterranean food in Washington DC. The company is known for its superior talent management practices, where employees are taken care of, and even compensated for sick leaves. They started infusing data science to their various operations, but soon realized, that the approach to a restaurant needs to be very different. Data needs to be used to get an analysis, but the final decision needs a human touch. As Cava Grill grew, adding new branches, the firm started experimenting with data to help line move quicker. It was understood then, that the personality of the person manning the counter makes a massive difference. Unfortunately, data mismanagement is part-and-parcel of several larger organizations, which could do with learning from the approach of Cava Grill.
Uploaded Date:08 February 2018
Machine Learning can help B2B Firms learn more about their Customers
Most of the business litany around the digital economy has revolved around customer facing organizations. This has involved literature on how companies are conducting business analytics by leveraging data from social media and e-commerce platforms to make more informed business decisions. However, there is another side to this business evolution. Beyond the customer-facing ones, it is also the companies engaged on the B2B who are extracting relevant analysis from these huge data troves which they traditionally lacked. AI techniques also help clustering individual buyer personas. Organizations like Ever String are using such data to provide meaningful business intelligence to firms like Autodesk. This particular tool is known as Enterprise Business Agreement Propensity Model which is particularly helpful to the company’s sales staff.
Uploaded Date:06 February 2018
Driving Value in Talent processes using Analytics
One of the key transformation occurring in the present phase of HR 3.0 is the process of talent recruitment being done not through individual sieving through thousands of resumes, but instead through artificial intelligence and business analytics based tools. FMCG giant Unilever is one such organization that has taken drastic steps to do this by using ads on Facebook from where interested candidates can fill out their details simply using their LinkedIn profiles. This is followed by a series of online games to test their aptitude and then video interviews through the company app or website. In fact, a study conducted by McKinsey’s People Analytics division has proven that their algorithm can screen resumes effectively far better than human beings can. Their biggest strength here is the ability to look past inherent human bias. While automation has been around in HR processes for a while now, the deployment of such analytics is the next step.
Uploaded Date:19 January 2018
How Companies are already using AI
Periodically now, reports and articles emerge condemning Artificial Intelligence (AI) for job losses. A study by the Oxford University states that nearly half the known present jobs would be lost by 2033. The OECD meanwhile claims that 9% of the jobs in its twenty-one member states could be lost much earlier. Management consulting giant McKinsey too states that job losses could be pegged at five percent. However, deeper introspection of available data tells us that more than automating human jobs, AI is actually engaged in machine-to-machine tasks. Such transactions are the low hanging fruits of this field rather than the mass people displacement as fear mongers have suggested. IT, marketing, finance and customer service are broadly the four fields in which majority of the world’s companies are investing in AI for. Three broad methods have been identified to locate these low hanging fruits. The obvious first one is to use AI in fields with an instant return on revenue and cost. An example of this would be Amazon’s use of AI to detect frauds. Certain opportunities need to be identified where the talks could be accomplished using the same number of people as involved presently. The Associated Press (AP) for example automated a large number of factual stories to its AI usage to increase footprint without affecting any employment. The business transformations attempted must start with the back end operations and not the front office. This is because front end operations such as sales or customer service require empathy and touch ordinary lives on daily basis.
Uploaded Date:10 July 2017
How AI is Streamlining Marketing and Sales
When legendary mathematician Alan Turing, fresh from his World War II success of decoding the German Enigma first devised the Turing Test, it was barely conceivable that a machine could outwit a human’s intelligence. Now not only are machines regularly passing such tests, they are actually being seen as a threat to human employment. However, this grave fear need not be so as shown through the Century Link example. As one of the largest telecommunications firms in the US, Century Link has for long been in the business of transferring sales leads to clients from various sources. This year they invested in an Artificial Intelligence (AI) enabled tool called Conversica. It uses a virtual assistant Angie to scan through 30000 plus emails in a day and provide business intelligence on the sales leads after interpreting those mails. It was found out that Angie could interpret 99% of those emails without human assistance and there was a twenty times revenue generation per dollar spent on the tool. Similarly Epson America was getting a large number of leads from numerous sources but started using AI to streamline the entire digital marketing process and empower the sales team with more qualitative leads. Wentworth and Rapid Miner are two other companies with similar roaring success in using AI.
Uploaded Date:10 July 2017