Key Product Management Principle - People are the core Asset

2017 is turning out to be a tumuntous year for IT industry worldwide. Large established IT companies such as Cisco, HPE, Dell-EMC, IBM are serious cutting down costs.  Unfortunately, companies tend to look at people as "expenses" and layoffs have become common.

Product managers have From a product managers often answers three main questions:

1. Where is the Product Today?
2. Where do we want to take the product & by what time?
3. How can the team get the product there?

Therefore, product managers have a different view when it comes to employees. From a product development perspective, people are "assets" - especially engineering teams and customer facing teams. Success of new product development depends of people.

Product managers treat people as true assets as the success of the new products - which creates future revenue for the company. Without people, the new product will never be able to reach its intended goal.

In IT, engineers and their intellect, skills, knowledge, character, integrity are - the true value in any organization. Because of the nature of IT product development, it is vital that product managers treat their engineering colleagues as true assets.  Product manager must spend time with the team. This means talking with them, listening to their concerns and fears about the current phase of the project, and occasionally taking them out for lunch. ( Lunch is a truly amazing way to motivate people)

Product managers have to make the team members feel valued. That's when engineers they care more about the product on which they are working. Face-time with the team also helps product managers understand individuals and personally assist them. Time spent with the team pays financial dividends as high-quality products make it to market on time and with enough vitality to excite the sales force.

Closing Thoughts

When product managers focus on the people with whom they work, the products succeed as a result.

Looking into the future - Right through Automation & Artificial Intelligence

Its no secret that Innovation & creativity is the ultimate source of competitive advantage. But success of any innovative idea depends on a number of other factors: An energetic leadership, Market growth, Significant investments pool, and a real "can do" spirit of the team.

As I write this article, there are thousands of articles being published on web - which state how robots and Artificial Intelligence will replace humans in workforce.

1. McDonald's is testing a new restaurant run completely by Robots 
2. Robot lands a Plane. 
3. Driverless Trucks will eliminate millions of jobs  
4. Smart Machines will cause mass unemployment  
5. Google's AI beats world Go champion in first of five matches  

Today's news is filled with the hype and fear of mass unemployment due to Automation. Today the hype cycle is almost at its zenith and in this background, I was asked to talk about what kind of jobs & employment opportunities will be there in future.

How automation will help mankind?

Automation is actually an innate feature of mankind. If we look into our past, we as a species have always come up with creative innovation to automate mundane tasks, and every time we did this, the civilization progressed by leaps and bounds.

The first ever automation was creation of canal system - thereby automating the transportation of water. This led to the rise of early civilizations in Indus River valley, Egypt, Babylon & China. Since then, civilization has been making a steady progress to automate simple, repetitive tasks.

Simple machines replaced human labor, trains & cars replaced horse drawn carts, Computers replaced clerks, and the list goes on and on.

From all our learning's, we know that if a task can be automated, it will be automated. There is no way a civilization will be able to stop automation. People have no pleasure in doing repetitive labor and the society will promote automation. Period!

And Yes, Today, People are being replaced by algorithms, machines and artificial intelligence.

What shall humans do?

As automation, artificial intelligence, machine learning and robotics grow in capability, humans doing simple, repetitive jobs will be pushed out of their jobs. So what will humans do?

The answer to this question can be found in history. When canals were invented, farmers found themselves with more time on their hands to increase the land area under cultivation. This led to more food production and this freed up people to create some of early classics of literature. Ramayana, Mahabaratha, Upanishads etc. were written during this time. People built massive temples, pyramids, palaces, forts, statues etc.

Industrial revolution also led to an explosion in arts - mainly paintings, writing of novels, poems, sculpture, building of palaces, classical music etc.

In 20th century and early 21 century, automation led to more creativity in terms of space travel, adventures, film making, music and new machines.

All this points towards only one direction. When humans are freed up from mundane tasks, they will use their free time to harness their creative potential.

Humans are innately creative. Machines, computers & Robots are not creative. Humans are far more creative and this creativity cannot be reduced into an algorithm & automated. This implies that the new generation of humans who are trained to be engineers, doctors, scientists and artists etc. will dream up new things to do, build and explore. Perhaps we may discover how to travel faster than light.

How to prepare for the new future?

The current education system is designed to create a workforce of yesterday, and people who do mundane, repetitive tasks and this education system will have to change first. We as a civilization will have to train the younger generation to be creative, develop expansive & divergent thinking. We need to nurture and flourish the creative side of humans and this will free up the younger generation to be creative and innovative.

Modern workplaces also have to change in a big way. Traditional hierarchical top down management system which pigeonhole people into narrow jobs need to be revamped. Silos need to be broken up and creative ideas must be fast tracked as quickly as possible. Businesses must be willing to take risks on new ideas. For example, Ford Motors recently fired its CEO - even after record breaking sales - because Ford as a business now needs a new business models - far from the one of building cars.

Cost of Failure - A major war & conflict

History also tells us the dark side of automation. Whenever automation ushered in a new era, lot of people had too much free time and when this was not utilized in a positive way, humans resorted to war and violence.

In fact, both world wars were in a way caused by industrial revolution. Industrialized European countries had surplus human labor and young population which had nothing much to do and the countries rushed headlong into a catastrophic war.

Today, we are seeing a massive surge in terrorism from people in Middle East and Pakistan. This is because their governments have failed to utilize their workforce in productive ways. Similarly, USA & China have increased their military spending in recent times - as they are not able to channel their enormous economic resources towards creative work.

Closing Thoughts 

We as a civilization are at the cusp of a new revolution - ushered by Automation & AI. Will this result in a golden era of creativity & innovation or will it result in a catastrophic war?

I cannot predict the future, but I know for sure that if we invest in building a creative & innovative society - we can usher in a golden era, else we are doomed for a devastating war. 

6 Key Tools and Techniques for Taming Big Data

Using Big Data across the enterprise doesn't require massive investments in new IT systems. Many Big Data tools can leverage existing and commodity infrastructures, and cloud-based platforms are also an option. Let's take a look at some of the most important tools and techniques in the Big Data ecosystem.

1) Data governance. 

Data governance includes the rules for managing and sharing data. Although it's not a technology per se, data governance rules are enforced by technologies such as data management platforms.
"There's a lack of standards and a lack of consistency," explains Doug Robinson, executive director of the National Association of State CIOs (NASCIO). "There's certain data quality issues: Some of the data is dirty and messy and it's non-standardized. And that increasingly has made data sharing very difficult because you have language and syntax differences, the taxonomy on how information is represented.

... All that is problematic because there's no overarching data governance model or discipline in most states. Data governance isn't very mature in state government nor local governments today, and certainly not the federal government."

Data governance is critical to gaining buy-in from participating agencies for enterprise-wide data management. Before data sharing can begin, representatives of all participating agencies must work together to:

• Discuss what data needs to be shared
• Determine how to standardize it for consistency
• Develop a governance structure that aligns with organizational business & compliance needs

2) Enterprise data warehouse. 

With an enterprise data warehouse serving as a central repository, data is funneled in from existing departmental applications, systems and databases.

Individual organizations continue to retain ownership, management and maintenance of their data using their existing tools, but the enterprise data warehouse allows IT to develop a single Big Data infrastructure for all agencies and departments. The enterprise data warehouse is the starting point for integrating the data to provide a unified view of each citizen.

3) Master data management (MDM) platforms. 

With data aggregated into an enterprise data warehouse, it can be analyzed collectively. But first it has to be synthesized and integrated, regardless of format or source application, into a master data file. MDM is a set of advanced processes, algorithms and other tools that:

• Inspect each departmental data source and confirm its rules and data structures. Identify and resolve identity problems, duplicate record issues, data quality problems and other anomalies 
• Ascertain relationships among data
• Cleanse and standardize data 
• Consolidate the data into a single master file that can be accessed by all participating organizations
• Automatically apply and manage security protocols and data encryption to ensure accordance with privacy mandates

4) Advanced analytics and business intelligence.

High-performance analytics and business intelligence are the brains of the Big Data technology ecosystem, providing government centers of excellence with a comprehensive analytical tool set that leverages extensive statistical and data analysis capabilities. Through the use of complex algorithms, these platforms quickly process and deliver Big Data's insights. Functionality includes the ability to:

• Mine data to derive accurate analysis and insights for timely decision-making
• Create highly accurate predictive and descriptive analytical models Model, forecast and simulate business processes
• Apply advanced statistics to huge volumes of data 
• Build models that simulate complex, real-life systems

5) Data visualization. 

Data visualization tools are easy to use — often with point-and-click wizard-based interfaces — and they produce dazzling results. With simple user interfaces and tool sets, users of advanced business intelligence and visualization tools can easily:

• Develop queries, discover trends and insights
• Create compelling and dynamic dashboards, charts and other data visualizations 
• Visually explore all data, discover new patterns and publish reports to the Web and mobile devices 
• Integrate their work into a familiar Microsoft Office environment
   

6) Specialty analytics applications. 

Multiple analytics techniques can be combined to deliver insight into specialized areas such as:
Fraud, waste and abuse. By detecting sophisticated fraud, enterprises can stop fraud before payments are made, uncover organized fraud rings and gain a consolidated view of fraud risk.

Regulatory compliance. Analytics tools can help agencies quickly identify and monitor compliance risk factors, test various scenarios and models, predict investigation results, and reduce compliance risk and costs.

HR analytics. Hiring is critical to build capabilities quickly. Therefore it becomes important to hire employees who can meet its requirements and fit into its corporate culture. There in lies the challenge: "How to hire someone from outside - who has relevant knowledge needed in banking and who will fit in with the existing corporate culture." This challenge can be solved by using data analytics during the selection process.

Each BU will have several such tools and techniques that are important, but that can't be justified to create data silos. Breaking data silos, combined technology with analytics expertise, new organizational workflows and cultural changes to enable enterprise-wide data management.

Developing an Innovation Zone

Every business today wants to be innovative. Yet most companies fail to innovate. Having worked as R&D engineer in Silicon Valley - where I started my career and filed for my first patent, and a innovation coach, here is one the key point for building an innovative teams.

Innovative teams need market knowledge to be successful. Having just technical skills is not enough. Here are four key inputs innovative teams need.













1. Customer Insight 

Great innovative companies such as Intel, Hewlett Packard, EMC etc have developed multiple channels to get information about and from customers, and have built extensive knowledge sharing systems to distribute this information widely within the company. This enables teams to understand customer needs and that helps develop new products that delights customers.

Having deeper customer interactions also provides opportunities for customers to participate directly in the innovation process.

2. Global Network

Companies that leverage information from the large business ecosystem are always at an advantage. Organizations that build a global network have greater advantage. When we look at top 10 innovative companies - they have a global foot print with teams operating in all continents and many countries, they integrate these global sites with information sharing channels helping teams all over to innovate.

The global network extends to global partners in the business ecosystem. For example Intel works with Hewlett Packard, Dell, IBM, Lenevo, Microsoft and several hundreds of partners to collect information & knowledge from the ecosystem.

3. Future Foresight

Innovation does not happen without a need from the market. Understanding what customers will need in future. But getting to know what customers will need in future is not easy. Developing a future insight in extremely difficult. This is where global companies have an advantage.  Identifying tomorrow's market needs, opportunities and risks requires working with senior management to assess the strategic and tactical implications of trends, and sharing information throughout the organization. Company leadership then shares this vision of the future with the entire organization. Global teams then work on this insights to develop products for the future.

4. Innovation Organization

There is tremendous innovation potential residing in all employees. Companies that go to great lengths to hire intelligent employees and then they have to empower innovators. Innovative companies provide dedicated R&D budgets, invest in labs, and focuses on innovation.

Company leadership backs up an idea with money, resources and time to develop innovative products.

Closing thoughts

All successful companies have reached the top because of their innovation. There has been no shortcuts in innovation.

Innovation is essential for success, but not all innovative products will be successful. For example, Nokia invested in two different smart phone technologies - Symbian and MeeGo, and yet failed. While history will say Nokia as a leader who failed, history will always remember Nokia as an innovative company.

How Startup can create a fast learning organization

In today's fast paced startup environment in Bangalore, startups such as Flipkart, OnMobile,  OLA etc. are facing a rapidly changing environment. Competition is fierce for these startups as they try to disrupt the market. 

Like with any startup money is tight and these companies have the challenge of hiring the right talent. In many cases, it is tough to attract talented folks - so they are forced to work with what is available. 

In such an environment, working hard is absolutely necessary, but it is not enough. It is also important to create an organization that can learn new things and adapt quickly to take advantage of new opportunities. These companies will have to be creative and innovative. Managers will have be bold enough to try new things, develop new processes and solutions and things don't work, managers must learn to fail fast and turn around quickly. 

Startups cannot afford to create a training department and formalize a training program. Instead, it is best to create a learning culture - where employees have the space to learn new things and have the opportunity to put their learning into practice. All this happens along with day-to-day jobs and without missing a beat.   

In order to create a learning culture, there are few things entrepreneurial leaders can do to create a learning organization.   

1. Top Management Commitment

2. Foresee future business needs and communicate to the team

3. Create space & time for learning

4. Encourage collaboration 

5. Encourage experimentation

6. Fail Fast, unlearn and relearn

7. Setup a reward system

8. Encourage Feedback

These steps will create an informal process for learning in a startup. As the organization grows and matures, it will be good to formalize the learning programs and have a formal training department. In this blog, I am focusing on startups - who need to bootstrap their teams to learn and develop new skills. 

1) Top management's commitment: 

Creating a learning culture has to be top down. A learning culture can be developed in an organization only when the top management is committed and deeply involved. At Open-Silicon, where I worked in the past, One of the founders was a professor and the other had a Ph.D. Both of them led by example when it came learning program. Starting off with such leaders, it was easy to imbibe a learning culture right from the start. 

2) Foresee future business needs and communicate to the team 

Top leadership of often involved in dealing with customers, vendors and partners. As a result, they will know the direction in which business is heading and will have fair idea of their future business needs. It is therefore important to share this insight with the teams on the floor and guide them into learning new things that will be needed in future.

Leaders must set a clear and firm learning objectives which is aligned to the business objective.  The strategic value of learning must be clearly articulated. Employees will be motivated to learn more only when they understand its importance and value.  

For example, when leaders in the IT department of a Bank learnt about the benefits of Big Data analytics, they created a small team - whose main task was to learn about Hadoop and see how Hadoop could change the current Business Intelligence (BI) operations. 

At Open-Silicon, Dr. Satya Gupta initiated a small team to go and learn all about new manufacturing process using 45nm lithography and see how it impacts the current design process. 

Leaders should encourage people on the floor the review new & emerging technologies and understand how it will help & benefit them. Without this guidance, any learning program will flounder aimlessly and lose steam.

3) Create space & time for learning   

Learning does not happen in vacuum. People will need time and space for it. This implies that top management must create the necessary time & space for learning. The best example in recent times was Google when it was still a startup. Google allowed its employees to spend upto 20% of their time on personal initiatives and projects. This created the necessary space for engineers to learn new things, try out new things and Google benefited enormously from it. 

Wipro and several other organizations conduct formal classes on weekends, where employees can sign-up to learn new things. Large organizations have collaborated with universities to create weekend programs that leads to Master's Degrees. Today, universities in Bangalore also encourage industry leaders to come and teach during weekends. I used to teach for Master's students at Manipal Institute of Technology. Teaching is a very good way to learn.

Startups can mimic the same model and help their employees learn - it can be simple certification programs or even university degree program. 

4) Encourage collaboration

Learning is best done in a group. For startups, it is not possible to create a personalized learning program or an Individualized development plan. Instead, it is best to network with other startups in the area and encourage collaboration between startups and have a joint learning programs. Collaboration lowers costs and encourages people to do more. 

Collaboration encourages employees to work in teams, share information, knowledge and learn through a peer group network. People will learn faster when they learn from others in their team.  

5) Encourage experimentation  

Learning without hands-on practical experimentation is useless. It would be akin to reading a novel. To get the benefits of learning and encourage employees, organization must allow for experimentation. Experimentation needs tools and resources. Startups have to provide adequate tools and compute infrastructure for experimentation.

Experimentation needs tools and resources. Startups have to provide adequate tools and compute infrastructure for experimentation. Experimentation can be in form of developing Proof-of-concept or even taking on a open-source projects.

For example, having a weekend hackathon will provide an opportunity for learners to try out their new skills. 

6) Fail Fast, unlearn and relearn

Learning is good for the individual, but for the organization learning a wrong tool or technology will not help. So leaders must watch out for such misalignments and wrong turns. When it is clear that the learning program is not aligned with future needs, the program must be killed fast. 

Leaders in startups have to be flexible and open to fail fast, unlearn things and relearn new things.  

For example, I had a case where a team was learning about MangoDB for bigdata analysis - but after few experimentation it was clear that this tool was not the right one. So the team quickly stopped all learning activities on MangoDB and switched over to Cassandra.

7) Setup a reward system

Employees who are innovative, creative, and experimental must be rewarded.  Rewards are always a great way to motivate people. Rewards is way of acknowledging that the learning program adds value to the core business.  Best part of giving rewards in a learning program is that rewards need not be cash based. It can take several forms - for example a plaque or a certificate or even a preferred parking spot etc.

Like in all organizations, rewards must be given judiciously and must be merit based. Having a regular rewards program will keep people motivated to learn more. However, one must be careful to ensure that the learning program rewards are not linked to performance at work. Regular work and learning should be kept separate. Also avoid giving out too many frivolous rewards. 

8) Encourage Feedback

If leaders in a startup keep a close eye on the learning program, then they will have valuable feedback. Yet there is a need to formally collect feedback on each program so that programs can be improved further. Feedback also helps to identify & remove any barriers to learning. Constant feedback and improvements will create a continually learning organization. 

9) Encourage a Teaching Culture

Learning cannot happen without teachers. So encourage senior employees to reach out and teach. Developing a cadre of coaches and mentors to help employees.  Caches and mentors love to teach - because teaching is a great way to learn several new things. Teaching a course helps people learn new skills such as pubic speaking, presentation skills, interpersonal skills, empathy etc. 

If business leaders act as mentors and coaches, organizations will becomes a learning organization - and will know what it takes in terms of time & resources.

Closing Thoughts

Building a fast learning organization is too important to be left to HR department. While large companies have a formal training department and with dedicated budgets, startups will have to be more creative and flexible.

It is very important to inculcate a learning culture at the startup phase itself so that all employees know the value of continuous learning. As the organization grows, it is important to formalize many aspects of employee learning and have proper organizational controls to oversee learning.

In this article, I have focused on learning in startups. If you have suggestions & feedback - please send it to arun.kottolli(at)gmail(dot)com.