Ahren E. Lehnert joined the Synaptica team a year ago to lead on Text Analytics Solutions. With 15 years’ experience in taxonomy management, he ensures our text analytic solutions work with taxonomy and ontology management, Linked Data, auto-categorization, knowledge management, and search to provide complete end-to-end content analysis solutions.
Why did you choose to work with the Synaptica team?
AEL: I have been working in taxonomy management for several years both on the consultancy side and as an in-house employee with organizations. The one role I hadn’t explored was the vendor side developing the technology and software, providing the solutions. In my previous roles, I had worked closely with vendors, assessing, comparing products, and discussing options. Experiencing what vendors do–knowing and understanding their world but not being part of it–was intriguing and to some extent attractive.
There was also a personal relationship with Dave Clarke, whom I have known for several years. We met at events and conferences and we had some great conversations. I have also known other colleagues who are part of the team. Jim Sweeney and I have crossed paths. I liked what the Synaptica team were saying and I respected their industry intelligence.
The final reason was definitely the reputation of the company; it really does proceed it. I had always heard good things about the company. It showed that not only was it great to work with them from a customer’s perspective, but the software was great. The fact that people mattered as much as the product made the difference. Relationships were key, and the team are helpful and honest. Synaptica is a company that soft sells its product as well as reputation. This approach was a good fit for me.
What did you do prior to Taxonomy Management?
AEL: My first career was as an English teacher. Teaching is challenging: the workload, commitment, pay, and school experience. I really enjoyed teaching, but at some point I grew disillusioned with the profession. As I had an English degree in teaching, I considered the alternatives. Then I joined the Modern Language Association as an Assistant Thesaurus Editor. I remember that when I went to the interview I told them I didn’t really understand what the job was; I didn’t get it at all. I often call the MLA my kindergarten for taxonomy work. Everything I learned about taxonomy started here. My involvement in the Information and Knowledge Management industry started here. I also got to know key people in the sector like Joseph Busch. It’s Joe I credit with directing me towards consultancy. I joined a large firm and the timing was perfect for me. Taxonomy was starting to grow in awareness and being with this type of company shaped my learning further.
Following this, I worked for several consulting companies. The skills you learn are what you expect: shaping projects and helping diverse organizations resource their taxonomy management projects. I found the consultancy side exciting as you had a different project every few months and you were working with new, diverse clients and often in a new location. After a while, though, I had some burn out from too much travelling. Then I went back into a working for organizations doing full time content management and search.
Although I had worked in taxonomy management for several years I got to a point where I wanted to know more about Text Analytics. This was a bit of a pivot, same field, same industry but moving to understand how analytics processes help you build your taxonomy and build information applications.
Tell us more about your current role with Synaptica?
AEL: I lead on the Text Analytics Solutions side. We produce software to manage taxonomy and ontology and with this you need text analytics and text mining functionality. As I have substantial experience in this field, it was a good fit to develop effective solutions that can work with our existing software. It’s very much part of our ethos to continually research and develop our products.
We are a small organization distributed globally and we work virtually across a variety of time zones. As well as the product management side, I also take a strong interest in our marketing and business development, particularly as we continue to grow as a company. This can mean anything from updating the website to writing a blog and sharing ideas on social media.
What does a typical day look like?
AEL: Normally, there are daily meetings with my team and despite being distributed across the globe we make it work. There is a challenge working virtually, but we are successful at it. As a Senior Manager, our roles are quite broad and the knowledge of all our products is extensive. You are always learning and adapting. Our philosophy is that we all need to understand what’s needs to be achieved. My typical day can include looking at sales or preparing demos for clients. I also work on specific proof of concept for customers, getting to know and understand their needs. From this product perspective, you need to work on what you want from the products and the functionality that’s needed. Then we need to discuss enhancements and modifications with the product development team.
Currently I am looking at our core products KMS and Graphite, the latter being our ontology software built using a graph database. Now we are working on functionality modifications for KMS then we will move shortly onto Graphite and embed text analytics into this software. We need to make sure that each solution is easy to use and has the flexibility our customers are looking for like drag and drop options.
What is your biggest challenge?
AEL: We are all overwhelmed by the amount of information; some of it is mundane – pictures of your lunch posted on Instagram–to in-depth articles or research topics. A significant element of this content is textual based as semi structured text. Everything is written in words and language. A typical use case could be customers are writing product reviews with no format other than its text. They are using words and different expressions. There is no perfect version of this product review. It can be written in a variety of ways. We are all different. We want to go through this big body of content and see what people are saying. There is no good way to do this manually. You could hire 1000 people to read it and index it or you can use software that will plough through this information quickly to extract relationships, concepts, and information in a much smaller amount of time.
That’s really the big challenge we are working to resolve. Understanding large amounts of data, often unstructured, capturing the insights from it. You are kind of processing this vast body of content, whether its created inside the organization or externally and you are trying to harness it.
Which part of your role do you enjoy the most?
AEL: The creative aspect of developing text analytics solutions for clients. It allows you to be creative and innovative, challenge what you see, use your expertise. You understand how the tools work, think about what we can do that’s different – it’s often new and exciting. This user design approach is a very creative process mixed with practical pragmatic functional needs. I enjoy that mix of being innovative but also ensuring it meets its functional expectation.
What advice would you give to others who are developing a major project?
AEL: Well if you are starting to develop a product or project you need to know your landscape. For a product, it’s your competitors and the industry. Is there a need for your software oris it a niche space you want to fill. What is happening in the space already? For us, both taxonomy and text analytics, there is a lot happening in these spaces.
If you are an organization, you start on this path. You may already have some software or someone working on this already. Ask questions and map your internal landscape to find out where information lives. Find out who is doing what. Do you have a knowledge expert at the company? People can be valuable to this project. Do your audit.
What do you feel the market is missing?
AEL: The Text Analytics market is missing ease of use but also transparency. Even as someone who is a near expert in text analytics, I find the tools complex and often difficult to use. This seems to be across the board and the answer is not to make the software too simplistic. The user needs to know how it works and what is happening. It’s a difficult and fine line to walk combining a complex tool with an easy to use UI for the average person. I feel there is a real space to get this balance right.
What do you think are the biggest challenges for the future?
AEL: Similarly, there will be continual challenge mixing accessibility and ease of use for the user. When you look at apps on your phone or tablet they are a complex thing used in a simple way. It’s good that people are actively talking about AI and machine learning. These weren’t topics a few years ago and now they are being discussed daily. It’s no longer an esoteric concept. The market in text analytics, machine learning and AI is really exploding. The challenge remains making it accessible to people and getting right. For example, recently someone was struck by a self-driving car. This can be scary for some. How can you continue to talk about technologies without fear and not racing ahead too fast?
What are you looking forward in the future?
AEL: There is very little understanding but gradually people start to understand and utilise the tools more effective. Initially we saw this in relation to Taxonomy and I expect to see this knowledge growth in Text Analytics. A few years ago, people were asking what taxonomy management was and what to do with it. Now the questions have changed and they are more advanced. Individuals are using taxonomy for extremely complicated uses. I hope and expect the same form of change for analytics.
Synaptica Insights are regular use case blogs providing tools, tips and advice from our customers, partners and colleagues.
