Customer World

Recently, I had a chat with Kate Visconti, Managing Director of  Acumen Solutions, USA who takes care of the Sales Acceleration and Change Management Practice. She is also an Adjunct Professor with Santa Clara University, USA. It was an interesting & engaging conversation and here are the highlights of the discussion.

What was interesting to me was the points she made for successful adoption of technology in an enterprise - the importance of business process re-engineeering, change management as much the software or technology selection & upgrade itself and looking at the implementation itself thro' a customer lens.

I have believed for many years that these were the most critical aspects when it comes successful technology adoption & usage and often enough importance & attention is not paid within the organization and the stake holders to this area. Kate brought this out beautifully and reinforced this very well during our conversation.

Here is the summary of our chat:

Swami: How do you approach a technology implementation and what do you believe are key differences that you or your organization focuses on?

Kate: We always start any technology implementation with a first principle approach - how is the enterprise and their stakeholders currently thinking, feeling and doing with their workflow right now. We strongly focus on process innovation and not a run-of-the-mill implementation like other system integrators. We conduct multi-day workshops, build customer personas, enable collaborative  conversations across cross-functional groups to understand current issues and identify opportunities for optimization and automation. For us change management is as much important as the technology implementation itself. That's a key difference we believe we bring to the table & where I have seen successful technology transformation happen. 

Swami: When it comes to selecting or shortlisting technology platforms or software etc. and adopting technology across the organization, which are areas that are normally missed by them in your experience?

Kate: Most of them don't have an 'outside-in' approach and we bring that to play when we work with organizations. When a tech platform or software is selected, there is a lot of discussion on features, benefits etc. but very often during implementation, they don't see the technology from a customer's lens. We do a lot of shadowing to know how the current processes work, do customer research, customer experience benchmarking and often these are areas that are not often not given enough attention or missed most often.

Swami: Enterprises spend millions of dollars on acquiring licenses for tech & software and you have seen many successful technology implementations, adoption and transformation across enterprises, what do you believe is the secret sauce for their success?

Kate: What I have seen in enterprises where there have been successful technology transformation or adoption is that if there is an Engaged Executive Sponsor, the chances of success improve by at least 2 times! An engaged leadership committee which defines the vision & organizational priorities makes the next difference in the success as the technology road map, business outcomes and priorities get defined well. Engaged Stakeholders make the next difference - end-users, managers, executives, customers as they influence adoption and validate user experience across the enterprise. These I believe are the secret sauce to success and where I have seen this happen in organizations, things have been successful most of the time.

Swami: You also emphasize a lot on hand-holding the enterprises which your organization does after you implement the technology or software. That's a very interesting point that you make and in fact what kind of metrices do you track and for how long do you suggest one must do this?

Kate: I normally suggest we do this for 60-90 days ramp cycle depending on the scale and complexity of the project and implementation. We track a lot of metrices post implementation like:

1. Project Success - Both by way of budget and time
2. Adoption -  Quality of inputs that go into using the software or technology within the enterprise after roll-out - Timeliness, Completeness of the information, Not just no. of log-ins but demonstration of new user benefits and referrals etc.
3. Business before vs Business After - Benchmarking and looking at % increase in agreed business metrics, % decrease in, say, sales cycle or service cycle reduction etc.

These are some of the sample key metrices one should look at.

Swami: There is often an underestimation of the services costs which enterprises need to spend to make the technology transformation successful. There is a lot of focus on licenses fees, infra needed, maintenance & renewal fees etc. but much less attention is paid to services & costs associated with it. Right?

Kate: I totally agree with you, Swami. In my estimate, these may vary by project scope, complexity and these are directional just to give you a perspective that enterprises need to factor these services cost for a successful technology transformation - up to 30-40% factor for change management, engaged leadership, customer research, building alignment workshops, post implementation program adoption costs etc. These are over and above license fees and customization costs they would incur during the course of a 3-4 year project or program.

Swami: I saw that right at the start of our chat, you mentioned don't treat it like an IT project. What did you mean by that? 

Kate: I often quote from the point made by Forrester Research Chairman and Chief Executive Officer George Colony made on technology projects, that in this age it is transforming from IT projects to Business Technology projects thinking. This is a key difference to successful technology selection, implementation, adoption and usage. I also say - Don't treat it like an IT project but treat it like a customer project!

These three - Deep Learning, Personalization and Privacy are indeed oxymorons.  The fact that when they come together for contextualization, relevance and differentiated customer experience - privacy takes a back seat!  When Privacy takes centre stage, then Deep Learning & personalization take a backseat! The real question, is from a customer point of view, can they work in harmony? How do companies use them effectively?

What deep learning can do is well documented. When you listen to this talk by Jeff Dean on Large scale deep learning at Google, you will realize the power of its capability. The most important difference you will see is how Google has embedded that in its products and services.This then brings the issue of privacy to the center of the debate, as this is the data of the customer that Google analyzes & monetizes. However, when it comes to the synergy between Deep learning and personalization, all the data that is used to understand this customer, effectively means personalization can be done like never before. So, the next time you walk-in to your favorite store, or your bank, or your online store, or your health care provider - the personalization possibilities thro' virtual assistants can create a phenomenal experience to the customer. Hence, if deep learning helps customers make their life simpler, then what's the problem with privacy? I think if this is done with the permission of the customer, then puts to rest the debate.

However, this has a lot of learning for the other industries - as the customer pays and owns their products, unlike Google where products are sometimes used for free. Take for example an automotive brand - the applications of deep learning, personalization is phenomenal. With most cars fitted now with navigation systems and telematics devices, the data this can throw about the customer, their driving habits into their automotive platform is phenomenal. The driving habits, the engine data, travel data, innovative use of public data all represent great deep learning application opportunities for the automotive brands to drive personalization & differentiation. Here, privacy is something of little consequence or debate as any assisted customer service will only enhance the customer experience. The same goes with banks - where the usage of the mobile app, online banking, payment apps, shopping data  thro' credit cards, public financial data etc. will only create opportunities for deep learning applications and personalization for enabling personalized financial solutions.

The question really is not will they but they will have to do it soon.

We live in a complex world today where customers reach or talk or share their views about companies or the products they like, own or use or their experiences thro' a multitude of ways. The touch points, the IT systems and channels are quite fragmented. Each day there is a new one that comes-up and there are more new ones that will emerge too. And to provide expert solutions there will be many specialists who will there. Specialists by terminology, means they specialize in one thing and they may not know enough about the others. This creates "information islands" in companies & acts as a huge barrier to solve a customer's problem. Customers too are left confused or dissatisfied as disparate touch points complicate their interaction with companies, waste their time due to repeated or failed interactions & therefore delayed resolution of their problems.

But to configure an optimum solution, it needs "integrativeness" in individuals who bring this diverse set of data & knowledge together. It needs integrativeness in understanding, thinking and connecting the dots intelligently to identify patterns and solve the problem. No amount of technology or analytical insights or process can solve this problem.

For the sake of analogy, let's take status of healthcare today - There are hundreds of specialists like oncologists, gynecologists, cardiologists etc. The patient however wants to be diagnosed and cured. Period. The hospital provides an umbrella for the generalists and specialists to work together for a successful outcome - curing the patient- they want the best healthcare experience. The integrativeness is provided within the boundaries of the hospital where these expert doctors practice & thrive.

Integrativeness is increasingly going to become a source of competitive advantage for businesses & professionals to manage superior customer experience. Today, APIs-for example, are integrators between diverse systems, integrating internal data & external data is becoming the norm for superior analytical insights, real time business decisions & technology integration is becoming a reality.

The question people must ask themselves -"Do I practice integrativeness in the way I think & work?". They might not know enough about everything deeply but they must have integrativeness in their work flow thinking, accessibility & process to quickly connect diverse sets of only relevant data or resident knowledge in companies to quickly comprehend, develop insights and solve customers' problems.

Integrativeness can change the way customers are managed by companies and how solutions are effectively delivered for them. Integrativeness in individuals is about quickly identifying "match keys" for every problem and having a set of APIs in their brains to connect available knowledge assets within companies, accessing this across departments or specialist functions, succinctly creating powerful insights to deliver superior customer experience or solve a customer's problem like never before.

Because, they may not be experts in everything that they do, Integrativeness is the new normal around how people will need to learn & adapt at work. Else customers can see and feel the difference!