Big Data – plenty of it,… but still missing

Big Data is a big is a Big buzzword. Although it brings huge opportunities, the “hype talks” might miss lead you to wrong decision that Big Data is cure for all. The truth is pretty simple – Big Data can give those answers that are hidden within the analyzed data set.

Spring 2010, at a small Croatian town there is an unusual meeting going on in a factory that we will call PPP. The meeting room at the first floor of the administrative building, just next to the gray production halls, hosted a group of about 10 different people. Individuals in the room take part of a fiery debate about the presentation that’s been projected on the wall. The discussion of a group of people in white coats, most probably production and development engineers, is obviously driven by the two most active members, often arguing with conflicting views among each other. There is a few people dressed in suites. One would guess that those are consultants and the company’s management team. Part of that group is quiet; they are just listening, and nodding from time to time to show their mental presence in the debate. Two persons from the group in suites ask a lot of questions. Some other participants are very active as well. They draw on the board and answer the questions with lively gestures. Those are mostly members of the academic community that take part of one of the EU “cross-border cooperation” projects, which is actually the reason of this colorful meeting.

Data Explosion1
Digitak explosion visual art

Let’s add sensors
In order to improve the efficiency of the production process and product quality, PPP initiated enrichment of certain phases of production by additional sensors, PLC and SCADA elements. By increasing the number of sensors from 12 to 35 per production machine, PPP started one of numerous initiatives around the world that contribute to the enormous global growth of machine generated data, the one we like to call Big Data. At one point, a temperamental professor with a French beard took stage. He passionately explains to the group recent results gathered from mining of the newly established data sets based on the increased number of sensors. No matter how colorful graphs were clear and despite the insight that was much above the previous findings, it was hard not to recognize the indifference on the faces of other participants in the meeting. Something is missing!

Data model or a Swiss cheese?
The whole initiative should provide, if not revolutionary, then at least usable insights. “We need to close the circle!”. All of a sudden, eyes of the participants were turned on the consultant who had been silent so far. “We need to close the information circle. You have all the parameters of the machine, but you really should start from the goals. You have to ensure traceability and link quality of the products with different stages of the production process and their parameters. Otherwise the new parameters won’t have much to say.” It is difficult to add IT tags to the hot metal castings that are being produced by the machines at PPP, so the data that was supposed to link the quality achieved and the level of waste with the 35 newly established parameters was simply missing.

Big Data: new methods, old constrains
Concluding superficially, Big Data might be perceived as a cure for everything: “now that we have so much information available, it is enough to develop mathematical algorithms and we will find all the answers.” But the truth is exactly the opposite. Today we have plenty of mathematical algorithms – from those that recognize your face, the tone of your voice or your fingerprint to those which understand the context of human speech, but the ways in which we traditionally collect data (processes) are not aligned with the technological capabilities of finding data patterns and filtering it through massive parallel processing (technology). More specifically, Big Data technologies will surely find patterns through a large amount of data, but those will not always propose answers to your problem or give you new relevant insights. In the same way, the data mining in PPP provided insight into the machine behavior such as stability patterns of certain parameters during the production cycles, including some insightful deviations. But it offered no answers about how those deviations and patterns affected the only thing that really mattered – the quality of the product. The answers must be included somewhere within the data set that we explore. They have to take part of the meta model of the entity that we analyze, or we must be able to deduct it from attributes of other entities that are similar enough to the one we study (i.e. the data on the quality of the product of hundreds of similar or identical machines worldwide, in case of PPP).

You can read more in the May 2013 issue of the Mreža magazine (Croatian language only), or later during the year translated to English at Alen’s Thing Place.

This work is Copyright of Alen Gojceta. You are not allowed to use the article, or any of its part in commercial or academic work without citing the author and this link.

Summary of the first year of Alen’s Think Place

The first full year of Alen’s Think Place is represented by 12 peaces of written work. Here are the summaries and links to 5 business articles translated to Englsih, 5 blog posts and 2 reviews of positioning / branding strategies…

The 2010 was the first full year of Alen’s Think Place is represented by 12 peaces of written work:

  • 5 translations of my articles published in Croatian business magazines during the past decade. Mostly on CRM.
  • 5 classical blog posts. Some of those were quick thoughts, and some other were excerpts from my recent articles
  • 2 reviews of positioning / branding approaches (McDonalds and Cedevita)

Alen’s think place is meant for business professionals, mostly for those who deal with sales, marketing, CRM and business strategies in general. I hope that you have found value for yourself and that you will keep finding it at www.gojceta.com.

CRM education – the follow up

11/23/2010
I used the www.gojceta.com to write the follow up of the CRM seminar I hosed. The conclusions are interesting to any professional dealing with CRM.

The CRM seminar redesign – the whys and hows

10/24/2010
In this post I announced the facelift of my CRM seminar and shared some thoughts about the approach.

The “bdp Triangle” – my Article on challenges of telesales campaigns – (English translation), Liderpress, 11/2005

09/09/2010
The “bdp Triangle” is among my best sales concepts….

Cedevita tea: “Dad does it dissolve in water?”

06/27/2010
I just couldn’t resist to write the article about this unconsistent branding approach…

Redefining the concept of Alen’s Think Place – the imperative of consistency

06/15/2010
A small “Alen’s ThinkPlace” strategy: consistent content to the consistent audience using a single language…

My Article on Organizational Gaps in CRM (translated to English), Banka magazine, March 2003

04/26/2010
The article elaborates the problem of a “CRM organization”…

Story about Mr. S and the failed CRM project

04/11/2010
Small insight in my latest article published in Mreza magazine through a story inspired by a true event…

7 wisdoms for a successful CRM implementation

03/16/2010
English preview of the implementation part of my April article – the 7 wisdom for a successful CRM implementation…

My Article on CRM customization (translated to English), Banka magazine, September 2002

01/31/2010
The concepts from this article from 2002 are just today becoming really mature and useable…

“Tasting” the McCafe’ business model

01/18/2010
In 2010 this was one of the most read articles at www.gojceta.com. Check why…

My article on IVR systems – PART 2 (translated to English), Banka magazine, May 2002

01/11/2010
A pretty long article about Interactive Voice Response set in two parts. Still relevant, but with the major change about the handy nature of mobile Internet access. Read first the part one below 🙂

My article on IVR systems – PART 1 (translated to English), Banka magazine, May 2002

01/02/2010
Part one of the above article.

All of the work above is copyright of Alen Gojceta. If you use it in academic or professional publications, please cite the author and the respective sources.

7 wisdoms for a successful CRM implementation

In April 2010 issue of Mreža (www.bug.hr/mreza), the Croatian magazine for IT professionals, my new article on CRM will be published. Actually there are two articles, one about CRM implementation and the other about related sourcing options and the available technology choices. I post here the English preview of the implementation part – a 7 points resume of the proposed implementation advices – the 7 wisdoms for a successful CRM implementation:

A preview of my article from April 2010 issue of magazine Mreža (Network)

  1. Do not “implement CRM“, rather solve specific business needs (sometimes you will want to have it so badly just because others would claim to have it too)
  2. Understand the culture and motivations of individuals and departments and incorporate it into the design of your CRM (even the cleaning woman may have something against your concept of CRM).
  3. Focus on small victories on the road to your great goal (otherwise only the goal would remain, an empty project budget, and travelers tired of the journey).
  4. Describe the desired business outcome to the technology providers, rather than the solution it self (describing a solution is their job anyway).
  5. Manage change at all levels during and after implementation (without a goal, a reason, and a role, even the most persistent ones shall give up soon)
  6. Optimize the user experience of your CRM application (a bad user interface is a grain of sand that can ruin whole systems).
  7. Establish a process of managing your data (data does not know how to leave a client, enter the CRM system, mark it self, link within context and turn it self into information).

©Alen Gojceta

My article on call centers translated to English, Banka magazine, February 2002

Call centers represent the very hearth of a CRM strategy. Why do we need call centers? How do we choose it and what is the experience of those who decided to modernize their customer interaction environments? These questions and more I tried to answer in this article, published in 2002 in Croatian Banka magazine. I have translated it to English for the convenience of all English speaking visitors of this blog.

Call centers in the mission of customer satisfaction – the thing is (not) about technology

If you will use this text for publishing or academic pursposes, be so kind to cite the author and source: Alen Gojceta, Banka, 02/2002. Thank you!

Call centers today are unavoidable part of a successful strategy of advanced customer relationship management, known as CRM (Customer Relationship Management). In brief, CRM is set of rules, technological procedures and applications that companies implement, on large customer base, to simulate close relationship, which is usual between customers and small corner shops. Large customer base, in this case means thousands, hundreds of thousands or millions of users.

CRM strategy was built during early nineties in economies where keeping the existing customer base became a priority due to high penetration of products or services and existing strong competition.

Looking from this perspective, the CRM strategy is a natural process that can be recognized already on economic models of ancient world – when the logistics and human resources where not capable for new conquests (which where very often the means of economic growth), fortification and preservation of existing properties used to take place.

Concept of CRM today suggests technology as being in the “first line” of relationship with the customer. This technology include applications for managing marketing, sales and provision of user services, including communication channels that allow managing interactions with individual persons, belonging to a large customer base, who influence buying decisions or is involved in use of products or services.

The heart of CRM strategy

Call center, as technological solution for efficient and effective telephone communication with a large customer base, most often represents the very heart of a CRM strategy.

Choice of the most appropriate call center solution depend on the form and level of integration of business processes, number of daily calls, intensity of marketing campaigns, ratio between inbound and outbound calls and integration of different communication channels that would be used. As higher the quantity of calls (interactions) is, the more advanced Call Center technology has to be for management of inbound and outbound calls.

Users want to do business with organizations in a simple way. Take as example a bank customer that wants to know how and under what conditions to refinance a housing loan. By dialing a free phone number of the bank, he quickly gets the right person with the right information and, preferably, a solution to the problem in a form of revised contract received at his home the next day. Interactions as described are proved to assuring increased customer’s commitment to a bank that provides such fast and efficient service. Study conducted in 1998 by the JD Power and Associates on a sample of 10400 users of services of five leading U.S. credit card issuers, revealed that price was not decisive. The study showed that the quality of service was the key to retention and customer satisfaction. In this type of business, the service is reflected in three major elements: the quality of call center contacts, transparency in payment processing and perceived financial strength and confidence about these companies.

Exactly due to the need for fast and quality interactions, some invisible items of call center operations can be critical to success. As larger the call center is (proportional of the number of daily contacts) as important becomes technological side of the solution to enabling the business success.

Success factors

There are two magic formulas that indicate the success of a call center supporting CRM strategy: service levels, and customer satisfaction.

The level of service is measured in percentage of calls that are received and processed in a certain time frame compared to the total number of calls. The level of service of a call center is directly connected with intelligent call routing capability. This would ideally mean that the system automatically recognizes the phone number and the individual customer, anticipating his or her reason of call, and addresses the most appropriate call center agent to handle the call. If the most appropriate agent is busy, the system will, in order to preserve the required service levels, make a compromise and forward the customer call to the following most appropriate available agent. Thus, the system will try not to let customers wait too long or ultimately hang up the call. You certainly have that experience when, after your call, you keep hearing the famous “Wait a minute …” phrase for some minutes more than you can stand.

Such behavior is unacceptable for a service provider who wants to build long-term relationship with satisfied customers. Customer satisfaction is a direct consequence of the level of service, and other processes that affect the speed, quality and efficient customer service. Advanced call center technologies ensure that your call is not infinitely rerouted among agents and departments.

Also, after a caller establishes communication, the agent has to be enabled to perform the desired transaction, provide information or to start a process. Customer satisfaction depends not only on call center technologies. In addition, it is supported by a whole set of CRM applications and processes, including internal company organization. It is therefore important, when deciding about call center technologies that the platform is open and capable to integrate with different CRM applications.

Despite the fact that it is hard to intuitively perceive measurable results of usage of advanced call center technologies, the experience is positive. On larger call center solutions that engage fifty or more agent seats, advanced technology may affect increase of service levels to from 20% to 95%. It means that the number of calls not solved would be reduced from 80% to 5%.

Problem solving solutions

Faced with deregulation of the market in Eastern Europe and aggressive new competitors who where realizing multiple growth rates, one of the leading telecommunications company in its region find itself in situation of redefinition of their business model, including managing of relationships with existing customers. After decades of enjoying the benefits of monopolist position, the company was forced to change the approach.

Given the relatively low market penetration, the challenge was twofold: to attract new customers and preserve the existing ones. Preservation of the existing customer base was the task of the customer care department. For the first time in their history, they started to measure the effectiveness of the existing call center. The results were disappointing. In some periods, almost 80% of the calls happened to be lost or otherwise unresolved. Users where giving up because of infinite redirections of calls. The existing system was not capable to support traffic peaks, so it simply used to refuse the calls or let them for long waiting.

A decision was made to implement a call center solution with advanced technologies and intelligent call routing, where agents where divided into dynamic groups based on their expert knowledge and skills. Transformation that followed was amazing – calls where positively solved within first attempt in 90% of cases. Users were satisfied and, combined with the efforts of the marketing department; the service provider has adopted growth rates comparable with the new competitors.

This is just one of dozens of similar examples. One well known case concerns Capital One, the credit card issuer. PricewaterhouseCoopers brings this case in their book on the CRM (Stanley A. Brown, Customer Relationship Management). After strong growth rates of customer acquisition, based on aggressive pricing policies and marketing approach, Capital One has lost its pace showing below market average growth rates.
After measurement of customer satisfaction, they realized that the ineffectiveness of their call center significantly increased with the enlarged customer base. Due to the increased diversity of their products and services, the need for segmentation and customized approach became more important.

With the introduction of technologically very advanced call center in combination with advanced CRM technologies, the level of customer satisfaction increased significantly. The average length of calls as consequence of increased efficiency fell to one third of the previously measured.

The cost reducing factor

Modern Call center technologies do not only bring the benefit of satisfied customers. The same solutions that contribute to increased customer satisfaction reduce the costs of call center management, where human resources cover 60 to 70% of its total costs. Five to ten thousands of daily interactions make a very common number for a market of Croatian size. Such amount of calls can be generated by customers of a company which is among market leaders and puts strategic focus on modern channels of communication with customers.

Assuming an average call time of four minutes, saving thirty seconds per call, on pattern of 5000 calls a day, would mean saving more than forty man-hours per day. For the same functionality it would take five agents less. In the same way savings in network costs and other call center costs occur. This calculation is very approximate and does not include the distribution of calls during time, queuing, traffic peaks and a host of other factors. But the message is clear. Significant are savings than can be achieved by changing the business channel model. Good integration of business processes within the call center can significantly unload or even replace the traditional and costly forms of interaction with users, such as “brick and mortar” offices.

Call centers are a paradox of today’s business philosophy that is focused on close customer relationship. From organizational perspective they look like sophisticated, automated mass production factories, while their end product is intimacy of corner stores and, consequently, user satisfaction.

In the next issue of Banka magazine’s Computers and business, we will address technologies that enable automatic service provisioning, without direct client’s contact with the call center agent, such as IVR (Interactive Voice Response) and CTI (Computer Telephony Integration).