Understanding the Role of the Hacker, the Hipster and the Hustler on the Road to Innovation: Key Take-Aways from the 11th Annual New Product Innovation & Development: A Frost & Sullivan Executive MindXchange

By Rajiv Kumar
Senior Partner and Global Vice President
Frost & Sullivan





 

Among the wealth of innovation strategies and best practices shared at the event, we present some of the most useful and critical ideas from key sessions. But don’t take our word for it, read on for the event take-aways that the participants applauded and are most likely to bring back to their teams.
 
From ASK THE EXPERTS! Panel Discussion: Teaching an Old Dog New Tricks: Best Practices for Engaging Every Employee in Entrepreneurship and Innovation 
 
The event’s most memorable terminology: the hacker, the hipster and the hustler are the three types of people who can help companies to innovate more efficiently. Their roles:

• The Hacker is the content or product maker
• The Hipster is the customer experience designer
• The Hustler is the sales team that makes the deals

If your innovation team is lacking a certain skill, ask the functional leaders to augment with one of their team members. The key is to view innovation as a talent development opportunity that makes a conversation about resourcing easier.

To attract talent from various functions, hold information sessions and emphasize the benefits of participation in various innovation initiatives; career change or advancement as graduates bring newly learned skills back to their functional teams; knowledge and skills necessary to start a new business; and networking with local entrepreneurs.

Have top ideas go through an extensive three-month incubation process as part of the corporate accelerator. It is not uncommon for engineers who come out of the program to discover their true calling is to be on the business side and explore career opportunities in product management, for example.

From CHANGE AGENT: Using Artificial Intelligence to Drive Dynamic Product Innovation

 
Artificial Intelligence is driving product innovation – and the biggest areas that will be impacted are robotics, cyber-intelligence and hyper-personalization.

Analytics will continue to play a critical role in our lives and businesses in the future.

There are four kinds of data science analytics:

1. Descriptive Analytics – What happened and why.
2. Diagnostic Analytics – Why it happened.  Analyzes correlations and relationships.
3. Predictive Analytics – What will happen next and  when.  Ask: Can I develop predictive models, statistical real time scoring using data to forecast future trends?
4. Prescriptive Analytics – What actions should be taken and when? What if” questions to decide what to do.

If your organization doesn’t already have a Data Science Manager or Engineer, it probably will in the future.  What are you going to do with all that data you’re collecting?

Other key take-aways:

• In order to achieve some of the growth that we’re going to see in AI, we’re going to see a massive amount of capital that’s going to drive innovation
• AI is going to lead toward transformative innovation – not in the abstract, but in the everyday. It will transform your internal business, and it’s going to happen globally 
• We are going to ultimately have a strong relationship, even an emotional relationship, with our devices. How many of us, if we leave our cell phone somewhere, feel a bit lost without it?

From SUCCESS STORY: Why Intelligence, Speed and Leverage are the Keys to Unlocking IoT Value 

 
The top 5 implications of ongoing and accelerating digital disruption are:

1. Real time information is too late - predicting the near future is critical. We need to get beyond real time and move toward predictive models.
2. If it doesn't work on mobile, it doesn't work. Just stop.
3. Context is King - no two digital scenarios are the same. Just because you know my name doesn’t mean you know me. The context of the interaction is crucial.
4. Innovation is more than ideation. Invention + Execution = Innovation.
5. Insightful intelligence is the currency of the 21st century (Key question: How do I extract value from this data?)

How do you make data actionable and valuable? It involves intelligence, speed and leverage:

Intelligence: There are a lot of players, providing a limitless amount of tools for data services. Intelligence must equal shared risk; in other words, they need to own the outcome – intelligence needs to be delivered as a service
Speed: An average company with all the predictive analytics in the world takes 12-18 months to produce a data science model. A lot can happen in 12-18 months, especially now. Best in class performance now can put a data science model in place in 2-3 days
Leverage: Shift your thinking; don’t view your business as what you do, but how you do it. Businesses are made of core capabilities; you want to be able to draw on multiple verticals to be able to solve your problems

Critical Insights to Bring Back to the Team

In addition to the timely insights above, we asked the 11th Annual New Product Innovation & Development: A Frost & Sullivan Executive MIndXchange event participants to share their most valuable strategy or insight from the event—the take-away they would be most likely to share with their team. Their responses included:

• The need to create and invest in a separate innovation team
• Innovation = invention + execution
• Culture eats strategy for breakfast
• Different stages of innovation call for different metrics
• Activity-based metrics are okay early on, while outcome based metrics are needed later in the innovation cycle
• Innovation can be viewed as a value, not as an objective

From creating an internal organizational culture that supports innovation to leveraging and integrating technologies such as Artificial Intelligence and robotics to help drive innovation, a thorough understanding of these important trends and insights is necessary to drive not only innovation, but more importantly, transformational growth.