Tapping into the collective knowledge of the organizations and customers opens new worlds of possibilities at a time when new levels of innovation are required to not only remain competitive but to gain market leadership.
With the amount of data available to organizations today, all employees should be empowered to innovate, speed time-to-market, serve customers, and impact company margins. However, this isn’t always the case. First, information isn’t really knowledge and on its own doesn’t provide actionable insight. Secondly, the building blocks of information, data, reside in multiple systems, and data can’t provide much value on its own.
Before the advent of Insight technologies, it took a human to look at the data in one system, then look at data in another system (multiply this by 5 to 10 systems or more, for a single project), then think about the relationships between the data to create meaning from those combinations, and then manually consolidate, mentally correlate, and analyze the data. At this point, the knowledge becomes part of the subject matter expert, and easily available via communication with the SME, or it may be published in some form and stored, yet again, in asiloed system.
We’ve found after working with more than 400 organizations that this holds true particularly within R&D departments—where knowledge can truly be power. The power to place customers at the center of operations, drive innovation, increase efficiency and productivity, deliver new products to market faster, and increase sales and margins.
Mid-sized-to-large, globally dispersed organizations often face challenges gaining insight from data for precisely these reasons, leading to a state of “Insight Deficit.” In fact, a recent digital poll of engineering and product development groups, when asked about the ability to find and understand available knowledge, said that the majority (46 percent) noted that their biggest frustration was having spent time on a project only to find that the work had been done previously. This was followed by the inability to find subject matter experts, information spread in too many systems, and knowledge loss when employees leave. A frightening 19 percent said “all of the above,” while only six percent were not suffering these challenges.
This inability to gain the right insight at the right time can delay or even derail carefully orchestrated processes from regulatory approvals to sourcing raw materials to launching new products. If information cannot be used to its fullest extent – with true understanding and insight, based on a complete picture versus that of a series of data points – then innovation and productivity fail. This leaves the business to suffer lost revenue and brand equity, as well as face higher risks.
Transformational Insight technologies can break down information silos by connecting the data from different systems without costly integrations, and then, through information, connect experts quickly and easily based on the most up-to-date work.
- Without complex integrations or disruption to the business, these technologies can:
- Automatically surface and connect experts across geographies and lines of business
- Provide root-cause analysis of any product issue, component, resource, etc.
- Enable real-time, 360-degree views of any entity, whether a project, product or issue—in a single screen
- Leverage prior work to enable incremental innovation for faster throughput
- Examples in which organizations have put Insight technologies to use include:
- A personal health products company leveraging knowledge to increase innovation and avoid commoditization of its products
- A high-end electronics manufacturer leveraging product feedback within social communities
- A global restaurant company fostering knowledge sharing across the world to innovate new products
- A leading technology company creating product roadmaps that map to customer requirements as well as company goals, by enabling customer engagement and centricity.
In this article we will explore the top reasons behind R&D insight challenges, as well as thetransformational approach to overcoming these challenges – in effect, providing the right insight, at the right time, for every R&D employee.
Tribal Knowledge Is Inefficient
Knowledge tends to be “tribal” – islands of knowledge among small workgroups, long-term employees, and those who truly collaborate and network well. A number of very large organizations have spent millions to understand the “network effect” of knowledge, and try to connect employees more thoroughly via personal interaction. Communities have been deployed and intranets implemented, yet information is tribal and siloed within these systems. This is especially true in engineering departments where highly-educated, highly-skilled specialists work in small groups.
Who and Where Are the Experts
Working in a very large engineering organization, with multiple departments working on multiple aspects of product design and engineering, chances are most engineers have an idea of what the five to six people around them have developed and what they know. If they’ve worked for the organization for a number of years, this could extend to a hundred people based on work over time. What about the hundreds or potentially thousands of other experts in the organization? What information have they developed and shared? What kinds of product-related challenges have they encountered in their jobs? Who has experience trouble-shooting a particular problem? Some organizations attempt to solve this challenge with collaboration platforms that ask users to complete a profile or rely on resume data. Both end up stagnant and without updates.
Subject matter experts often remain untapped resources, resulting in lost opportunities for R&D gains in innovation, efficiency, and productivity.
Cross-Departmental Collaboration
As important as sharing information within engineering operations is, it can be even more important to ensure that information is flowing back and forth to other departments. Product engineering doesn’t stand in its own silo, and neither do departments such as customer service, sales and marketing. These departments generate their own information—particularly customer and market information – that can be vital to the product development and engineering functions, and vice versa.
Let’s take a look at areas which should contribute, ideally in nearreal-time, to R&D:
Customer Service: Feedback about new product releases, existing product challenges and adoption characteristics, coming from direct interactions via all channels, includingcommunities and social media. Early detection of challengescan mean big gains.
Sales: From those who are on the front lines and should be the eyes and ears of the organization – potential customer needs, desires and challenges they are seeking to overcome, with which your company could help.
Marketing: Market trends, competitive information and partner requirements, should all be taken into consideration during product development.
Finance: Information about purchase and payment histories can be extrapolated to uncover product trends. Useful to the entire organization, this information can be particularly valuable in product roadmap development and lifecycle management.
It’s a given that R&D and product engineering information should also be available to each department, helping to prevent customer challenges and issues, inform sales and marketing, and enable finance to accurately plan and forecast.
Insight to Innovate
Another symptom of “Insight Deficit” within R&D is lower levels of innovation. Engineers and developers generally don’t have access to the full breadth of information necessary to make informed decisions – product data, competitive insight, customer surveys, and more. As a result, products take longer to get to market, production requires more re-dos, and competition may often seem one step ahead. Without easy assimilation of relevant and actionable insights, organizations aren’t as nimble or flexible as they could be.
Having better insight into data across systems helps companies improve agility in their production processes. They can incorporate feedback from customers as well as internal review teams and can adjust processes and perhaps swap in new materials to improve each cycle of development. Having more insight into these facets allows product engineering departments to do a better job justifying the investments they make in R&D.
Employee Satisfaction, Ramp Time and Cultural Assimilation
All of the above scenarios – lack of knowledge sharing, productivity loss, and stalled innovation – can lead to an even greater issue: job dissatisfaction and low employee morale. Although employees seem busy – and may be working long hours without access to information that can speed up processes, productivity, and innovation – they are wasting time and effort. Their work will suffer and turnover can result.
New employees know little about who knows what or where to find information. Until they become assimilated into the culture of the organization – which often happens through personal interactions and understanding the organization’s knowledge assets and how they came about – they will not be productive. Access to the information required to do their work makes employees ramp up more quickly, and when employees are productive they are generally satisfied. Providing the right insights to new employees tells them they’ve joined the right company and will be successful.
Technology Shortcomings
Many organizations have found that the first generation of enterprise search, knowledge sharing, and collaboration tools have helped ease information access to a certain extent, but have not solved the challenge of data variety and velocity of change. Some tools, such as employee and customer communities, have created further information silos (albeit of highly valuable information) rather than truly collaborative knowledge sharing. The current move to the cloud further fragments the availability and format of data. Intranets, file shares, PLM, ERP, product defect databases, CRM, social media, and more all contain highly valuable information and yet require significant investments of time and resources to connect through traditional data movement and system integration projects. While legacy of enterprise search tools may aggregate search results from these highly disparate systems, providing some access to data, the results are less than optimal. These systems often fail to provide information that is relevant to the user, leading to low levels of adoption, and can even erode confidence in IT’s ability to keep pace with business requirements.They do not normalize, add structure to, or uncover the types of information relationships across systems, which are required to transform organization’s ability to leverage their most critical asset – knowledge.
Fortunately, with the more agile Insight technologies available today, there is a transformational alternative to traditional enterprise search, data movement, and integration projects. Connecting with the information where it naturally resides, regardless of system. Virtually aggregating the full variety of real-time data from across all of these disparate systems provides the ability to enrich it through normalization, correlation, and analytics. This has the power to provide employees (and potentially customers) with the right insight at the right time. By crawling this information and storing facsimiles of it in an always-on, intelligent index, Insight technologies correlate relevant information for particular roles, such as an R&D group working on a particular product, or R&D leaders from across the full universe of data. It is then presented in mashups, either from within a system that knowledge workers “live within” or within a separate console.
Whether the project entails connecting 5 or 75 systems, Insight technologies allow employees to instantly connect the complex dots between information that leads to innovative breakthroughs, discovering potential issues before they become endemic, tracking trends on recurring issues, feedback, and sentiment combined across multiple channels. Tapping into the collective knowledge of the organizations and customers opens new worlds of possibilities at a time when new levels of innovation are required to not only remain competitive but to gain market leadership.