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Technology meets marketing. Analytic mind meets creativity. It’s going to be a year of change which is just speeding up constantly
As we already know, organizations have ability to collect, store and analyze massive amount of data from multiple sources. They have spent a lot of money managing this big data. Investments in technology and analytics are useless unless employees can use data, information and knowledge in their decisions-making. Many companies are facing a big challenge in data-driven decision-making. Good and rich data won’t quarantee good decisions on their own. I posted May 2012 an article about Insight IQ. It was based on April 2012 issue of the Harvard Business Review where Shvetank Shah, Andrew Horn and Jaime Capella argue that Good Data Won’t Guarantee Good Decisions. In this article I continue this theme a bit further.
Shah, Horn and Capella found that there are three main types of decision makers:
- Visceral decision makers (gut feel decisions)
- Unquestioning empiricists (rely on the number alone)
- Informed skeptics (gut feel with data)
If we consider the matter in data perspective I defined simple data collaboration or data insight maturity scale. It emphasizes level and maturity of data collaboration in decision-making.
Organizations on the right ‘high side’ are capitalizing the data in decision-making. They combine the gut feel with data and can drive decisions that make a real difference in productivity and profitability. They can drive real competitive edge from and behind the data. They drive all necessary information from markets for better decision-making. They know their customers and customer journey. Although the decisions can be very complex with limited amount of time and there are many options to choose from, they can still make the decisions and carry out them fast. These companies are the winners. They have hit the jackpot, but unfortunately I see these kinds of companies quite seldom. However, that is the goal to go for.
Another way of looking at this variety in corporate behavior is to divide companies in three categories according to state of data maturity. There are three types of companies: data collectors, data analyzer and data innovators.
1. Data collectors
These companies are collecting and learning which data is important for their business. Light segmentation is used and it is more building and focusing on different customer groups. Analytical skills are very low and decisions are made as gut feel or based on basic sales figures and income statement
2. Data analyzer
These companies have systematic way of collecting and storing data. They are invested in the technologies that are available to analyze the data. They can do basic business reporting but are not able to drive the real value behind the data. They are good at analyzing and reporting but suffer the lack of interpretation skills to drive deeper business insight.
3. Data innovators
These companies are more comfortable with big data sets and technology. The focus is in how benefit from actionable insights and strategic big data. They have effective ways to share business information across functional areas that better decisions can be made. They have many data-savvy employees and data-driven decisions are informality in C-Suite.
Steps from data collector to data innovator
It is all about people, process and technology. Here are six steps to improve data-driven decision-making.
1. Emphasis on right data
- collect all relevant information into one single platform
- from business understanding to data understanding
- automate the data collection process
2. From silos to holistic business view
- map all the relevant data, which is essential for decision-making
- data preparation, consolidation and visualization are necessary
- CMO & CIO partnership
3. Choose the right technology
- find technology that meets your business demands
- choose technology, which accept and read data from any source
4. Online reality
- today’s business and business environment needs real-time data
- online data as enabler of quick decisions and insights
- rapid resource allocation
- online business management and intelligent decisions
5. Create strategic marketing dashboard
- KPI’s by channel
- true values from returns and investments
- identify risks and opportunities
- measure and lead the customer journey
6. Create systematic analytic skills competence development program for employees
- find the data-savvy workers in your organization
- make them to train everyone else of their analytics skills and method
- leverage analytics know-how widely in your organization
- C-suites as exemplary for others
Big data is out there. Data volumes, velocity and varieties have multiplied, in fact exploded. The big question is how to find the best ways to make all of it and how analyzed data is changing decision-making ways and management. Are big decisions based on analyzed evidence or intuition?
Many organizations are thinking how to drive the real business value behind big data. They are drowning with data and don’t know what to do with it. To drive competitive edge from big data, organizations need new competence and new management style. These are very big issues in today’s business environment and get accentuated all the time. For example, Gartner’s top 10 strategic technology trends for 2013 addressed strategic big data and actionable analytics. These two trends were number six and seven. And believe me, these two trends are raising top of that list the near future.
Ten years ago I created Intelligent Contact Management (ICM) concept at MicroMedia. It was holistic approach for sales and target marketing. The main idea was to translate inside and outside, online or offline data into information, information into deep knowledge, knowledge into action and action into measurable results. Action means in this case multichannel sales and marketing approach. Right and relevant message to right targets at the right time. Way of handling and managing touch points in customer journey. The concept of ICM presents in picture below.
Is there any significant changes in ten years. Nothing much, except tsunami of unstructured information has swept over. After ten years we are facing with information that comes in varieties and volumes we could ever imagine. That is not a threat, it is the big opportunity to handle and manage more precise information for predictions and decision-making.
Big data is a management revolution.
There was a very interesting article about big data and management revolution in Harvard Business Review, October 2012 issue by McAfee and Brynjolfsson. They wrote that “data-driven decisions are better decisions – it’s as simple as that. Using big data enables managers to decide on the basis of evidence rather than intuition. For that reason it has the potential to revolutionize management”. I could not agree more, using and analyzing data for evidence-based decision-making is the quantum leap from hunch and “super intuition”. This leap composes a big managerial challenge.
Are data-driven companies’ better performers?
There is a lot of buzz and skepticism about the real value of being data-driven organization. McAfee and Brynjolfsson made a research to find real evidence that using big data will lead to better business performance. They interviewed executives at 330 public North American companies about management practices, both organizational and technological and their annual reports. The major finding was that companies using big data and data-driven decision-making are performing better financially and operationally. In fact they are 5% more productive and 6% more profitable than their competitors. But, and this is a big but, 32% of respondents set their companies below 3 at 5-point composite scale when asking is your company data-driven. So, there is a lot of work to do in this field.
Destroy the empire of HiPPOs
Is your organization making decision HiPPO-style? McAfee’s and Brynjolfsson’s definition for HiPPO: the highest-paid person’s opinion. These executives are making decisions based on their experience and old intuitive patterns. The big question is are these executives ready to cancel their decisions if analyzed data is telling the opposite than their intuition and hunch. The answer is yes and no, but the big shift is happening. In today’s business world, executives can rely on data and predictions. The biggest factor is that they can ask the right questions. When the data-driven decision-making movement advances further, HiPPOs will mute and extinct. New data experts will arise. Future CMO will be this kind of expert in executive group.
Manage the big change
McAfee and Brynjolfsson picked up five management challenges when moving towards data-driven company and evidence-based decision-making.
- create leadership teams, set clear goals, define success and focus on asking the right question
- do not forget the human insight
- think creatively
- communicate clearly with employees, stockholders and stakeholders
- employ data scientists
- invest in technology
- update IT competence
- create cross-functional cooperation
- locate the big information and decision-making in the same place
- improve problem-solving techniques
- ask the right questions
- move actively away from hunches and instinct
- do not pretend be more data-driven than you really are
- forget the HiPPO-style decision-making
The big data will become a key basis of innovation, productivity and competition. According to research by MGI and McKinsey’s Business Technology Office there are five ways in which using big data can create value. First, big data can create value by making information transparent and usable widely inside the organization. Second, organizations can collect more accurate and detailed performance information, analyze it and drive performance. Companies are using big data and analysis to make better management decisions. Third, big data allows ever-narrower segmentation of customers and therefore much more precisely tailored products or services. Fourth, actionable analytics improve decision-making. Fifth, big data can improve the development of the next generation of products and services.
In the end, one rule of thumb to remember: Big data will never replace Big thinking!
Planning 3.0 – combining Creative, Communications, Experience and Business planning = Customer Journey Management
Admap published a writing competition results – best articles about “Planning 3.0”– How will we be planning in 2020? The winner, Nick Hirst said “We need to transcend the often polar disciplines of ‘conceptual’ (creative agency) and ‘practical’ (media agency) planning to deliver, not communications, but great brand experiences.”
I couldn’t agree more! Although mr. Nick Hirst’s and other rewarded articles were great, what really made an impression to me was the pre-words the judges wrote. They analyzed the articles they received and came to conclusion that the future of planning looks like… ‘We don’t know’, or at least, ‘we don’t agree’.
According to judges the most striking theme about the entries was not about how the entries were presented but how they represented a clear new chapter of planning, not necessarily a consistent chapter, but a new one nonetheless. This new era could be dubbed the, ‘the post-specialist era of planning’.
Planning has grown around specialists in data and analytics, user experience, information architecture, trend analysts, digital strategy search optimizers, social media and crm gurus… Until now, the dominant conversation about strategy has been about the need for these specialists, and for them to be distinct and separate from what has gone before.
Entries to this Admap Prize competition no longer championed the specialists as skill sets that deserve their unique place. Instead, they argued that they should be the very future of planning in its entirety; the planning specialism becomes the planning mainstream. According to judges, authors wrote of the data and analytics skill as simply becoming planning – all tasks of planning would become measurable and, therefore, the measurement/analytic skill would become planning. Or, the specialist skills of social media strategy would become the fundamental of brand planning, given the very social future that brands face.
According to main judge, JWT’s Guy Murphy two things will happen
1. There will be a sense of planning returning to be a more singular and holistic way of working. Certain planning tools will become the norm for all planners – just as the notion of ‘paid, earned and owned’ seems to have become standard currency for media thinking today.
2. Planning will become more influential. The assimilation of its new-found specialists skills will make it a richer, more effective and more confident force. It will make a decent fist of managing the huge and growing complexity that faces brand building and communication. This will shift the role it has been playing.
In my opinion 2020 is far far away and everything mentioned above is already happening. Planning is rapidly facing new requirements for its effectiveness and moving towards more holistic view. Actually this holistic approach is gaining momentum in general.
Last week IBM organized “Smarter business day 2012” event in Helsinki. Data analytics was an issue there too. What IBM’s director for Analytics division Juha Teljo presented that the whole analytics business is moving from application centered approach to analytics centered approach by 2020:
So, along with planning, also the whole infrastructure is becoming analytics – that is planning – centered. Once I search about this matter, I also found IBM’s view on how to create Analytics Center of Excellence inside your own organisation. The 150-page material is attached here: 5Keys to BA Program Success
The winning article by Nick Hirst agreed with this idea of holistic planning. He recognized User Experience planners as the first breed of future planners: “User experience goes way beyond Information Architechture. While the latter is a specific discipline concerned with the organisation of information to ensure its swift, intuitive navigation, User Experience considers the experince of the user as a whole: their expectations, their level of interest, their attitudes even how they feel. Concepts like surprise of disruption, or even entertainment – all proven tools for affective and effective communications – are anathema to a classical Information Architect, but entirely within the imaginative realm of the User Experience Architect.
Even now they think about both the effect of an indivicual, small experience – a piece of copy, a picture, the way a button workds – and the overall journey. Even now, some agencies are recognizsing the ‘planneriness’ of what they do, and reconceiving them as Experience Planners. But just imagine what would happen if we unleashed that kind of thinking on everything else that comms agencies do now.”
I think the future of planning will be even more amazing than expected and I do think that Nick Hirst’s dream is becoming reality. Here’s what I think:
- Planning marketing will be about planning competitive advantage, that is corporate strategy and operations. see Forbes article here
- Corporate Image will be more and more about actual experiences and shared opinions – planning will be about designing and managing customer interfaces and experience. Article here https://futurecmo.org/2012/11/10/marketing-do-or-die-managing-customer-interfaces/
- Comms and marketing to customers will become service experiences – event based automatic communications that integrate with the customer’s situation and needs in any given location or interface. Marketing automation becomes service automation along the customer’s journey. The center of gravity will be the Customer Journey understanding and design.
- Planning will become more holistic than ever – we are moving towards business design. At this point planners will become the McKinsey’s consultants of tomorrow or McKinsey’s consultant will take care of the business design on behalf of marketing planners of today. McKinsey is already moving towards customer journey and experience planning, see this article http://cmsoforum.mckinsey.com/article/winning-the-consumer-decision-journey#.UIOLl_Mukic.email I would take it even further, here’s why https://futurecmo.org/2012/10/21/customer-decision-making-journey-flow/
Companies that are taking analytics and planning seriously are already doing much better than their peers. By 2020 you really have to be great in order to survive. And let’s not forget – analytics is useless without understanding and decisions (generate corporate autism) – planning and management. I thinks this means the dawn for customer journey planning and management as the new breed of holistic planning work!
Author: Toni Keskinen, Marketing Architect & Customer Journey Designer
Join FutureCMO Movement LinkedIn Group here
McKinsey just published an article about customer decision making journey. It’s an approach based on a single research and 20000 respondents. I find it great that Customer Journey work and methodologies get real attention and McKinsey’s article proved that customer journey understanding, analytics and design are maturing and becoming real business management tools. We have taken it further with Jarmo Lipiäinen and created Customer Journey Management methodology for sustainable management model. We are also trying to have Customer Journey Management – the book – published, but in the mean while here are some thoughts about how to apply customer journey mapping and understanding to your business.
To start with:
You need to understand that there are very different journeys to begin with.
- Purchase journey (From awareness to consideration and transaction, Acquisition)
- Service journeys post purchasing (Using the product or service, value-in-use)
- Planned (e.g. Address change, regular maintenance etc.)
- Unpredictable (e.g. Product failure, reclamation, insurance coverage, etc.)
- Delivering a service as a customer journey (taking a cruise or flight, restaurant, using media, etc.)
- Retail customer journeys (e.g. IKEA store experience)
Media company’s customer journey would be about daily use contexts in multi-channel environment reaching the customers with online, print, tablets, email with variety of media types. The thing is, if you simplify customer journeys too much, you will not benefit from the analysis either.
1st: Concentrate on what they did
When you are diving in to customer behavior along their decision-making journey, you need to understand that only customers who have recently done the purchase can tell you how they did it. People are very bad at behaving according to their preferences – so you need to learn from what they did – not from what they think they would do. When people enter the decision-making journey – they can not know how they come out of it. Here’s an example of car purchases
When customers enter the maze they have certain brands in mind. When they are inside the maze they will consult professionals, read reviews, visit discussion forums and discuss with friends. When they are in the zone they will pay attention to advertising they normally ignore and they are likely to learn a lot. Eventually, when they buy something, it could be something they wouldn’t have thought in the beginning.
2nd There are dynamics – rules of engagement so to say – but each category and brand journey is different
If you consider decision-making journeys from buying a nuclear power plant to buying a bottle of coke – here’s how you can analyze the rules of engagement
The customer journey for a well-known, liked and preferred brand is extremely different from a journey for unknown new brand. Read more from article: Brand as a roadsign. It is also good to understand that if you have several product categories, each of them is likely to follow different dynamics.
3rd Look at the whole market – not just your own touch points and understand the market flow!
Here is an example of market flow for a telecom operator. The Dynamic market flow is interesting concept that medical companies are using. They don’t look at the overall market shares but dynamic market, which is about new prescriptions and changing prescriptions. Similarly, looking at the market change is where you can best see how your work is influencing. The market share will follow. Here is some idea about how the idea works from a telco case I made a year ago. I can’t give any actual data out because it is proprietary but I can explain the methodology. First of all, what is the size of dynamic market and how does it flow:
This data tells you how many actually bought, how many of them bought spontaneously and how many did considered purchases. Earlier I did a customer journey decision-making mapping for 3G bundles in Finland, Denmark and France. I can tell you that the differences in national behavior also vary very much. When French people make considered purchases, Finns buy 3G bundles like sausages. These two markets have very different dynamics. Ok. Let’s dig deeper. Here is how you can break down each product category:
This graph has very important information presented in a single page. I know it is not beautiful but it is highly practical. First of all you need to know whether people are newbies and making their first purchase or experience buyers. Then, what is it that makes people tick and initiate conscious consideration? When they do get activated, do they really look for more information or just rely on their brand related heuristics or do they just buy spontaneously? There is great different between customer journeys that are spontaneous and those that are considered. There is even more important figure to understand, that is outbound tele sales share of dynamic market. When you have all this information about your brand and your competitors, I can guarantee you will find insights and surely learn what to do differently. Between brands there will be major differences in conversion rates from preference to purchases and differences in sales via different channels: outbound, retail, online, inbound…
4th Different types of relationships
You buy milk several times a week, you use video rental service occasionally, but very rarely rent the same movie. In average you buy a house once in a lifetime. The relationships are different, very different. This difference has a major impact on how you can create customer relationships and apply customer journey methodology to them. Here are the variables:
These variable form a quadrant with typologies:
It is obvious that every brand should work their way up and to the right. Even if a customer only buys the product or service once in a lifetime, you could still create relationship that feels like continuous relationship.
5th Leverage all your information assets
Understanding the whole customer journey makes it possible for an organisation to re-define relevance and information sources. I’ve published an article about how to cure corporate autism earlier and you can find more from there. Check out
However, you need to understand how the market works and how does your products and services flow with the market. The Customer Journey as a full help in defining what to pay attention to.
Along the Customer Journey you can analyze customer behavior with online analytics, CRM, marketing automation tools, CSAT, VOC-studies, look at market data, research marketing and brand outcomes, analyze social media.. Ok, the list is endless. This is why you need to re-define relevance and build your KPI’s accordingly.
Business Dynamics Score is one of the most fundamental decision journey metrics. It tells you how many customer that preferred you originally, did you keep and how many did you lose. Of those who had no preference or preferred competitor, how many did you win or lose.
LAST but not least
If you really step in to your customer’s shoes, you understand that for a customer a brand is a single entity. If you really analyze customer journey you will find out what to change in order to perform better, but it could be anything. The challenge I have faced most often when I have done customer journey mapping and analysis for my clients is, that it is difficult to tear down silos and act on customer behavior needs. Instead of print campaign it might be better to spend the money on new online webstore, or investing in marketing automation software enabling event based servicing. In my opinion customer journey work is an extraordinary innovation methodology for corporate transformation, change management, and amazing performance.
Author: Toni Keskinen, Marketing Architect & Customer Journey Designer
Join FutureCMO Movement LinkedIn Group here
Big data is the catch phrase inspiring corporate management right now. I agree that it is the direction many companies should choose to take. However, the reality is that challenges are not in systems and technology. Most important challenges can be found from our own ways of working and thinking. In this presentation I explain what is corporate autism about and how to cure it. Please comment and give us your feedback if you find this approach eye-opening.
Author: Toni Keskinen, Marketing Architect & Customer Journey Designer
Join FutureCMO Movement LinkedIn Group here
I read a very interesting article from HBR, April 2012 issue. Shvetank Shah, Andrew Horne and Jaime Capella wrote an article about how good data won’t guarantee good decisions and most companies have too few analytics-savvy worker. If you are not able read that excellent article from HBR, here is a couple of points from it.
We have already discussed in this group about the new era of decision-making and importance of customer insight. Ability to collect, store and analyze the big data has grown explosively and companies spend a lot of money analyzing customer data. BUT. And this is a big but although you have the best BI tools ever but if your organization cannot capitalize it the investments are useless. Like Shah, Horne and Capella stated in the article: ”For all the breathless promises about the return on investment in Big Data, however, companies face a challenge. Investments in analytics can be useless, even harmful, unless employees can incorporate that data into complex decision-making. At this very moment, there’s an odds-on chance that someone in your organization is making a poor decision on the basis of the information that was enormously expensive to collect”
Shah, Horne and Canella created Insight IQ, method that asses the ability to find and analyze relevant information. They evaluate 5000 companies from 22 countries. The founding’s were interesting. Three groups were found: ”unquestioning empiricists”, visceral decision makers” and ”informed skeptics”
Companies are seeking for ”informed skeptics”. They are data-savvy workers who are able to make good decisions. They have strong analytic skills, ability to balance judgment and analysis. However, the study found that only 38% of employees and 50 % of senior managers fall into this group.
Shah, Horne and Canella identified four problems that prevent organizations from realizing better ROI in Big Data:
- Analytic skills are concentrated in too few employees
- IT needs to spend more time on the “I” and less on the “T”
- Reliable information exist, but it’s hard to find
- Business executives don’t manage information as well as they manage talent, capital and brand
Well, how to develop more informed skeptics? It demands constant competence development to increase data literacy and join information into decision-making. And of course, organizations have to give the right tools for analyzing the data. Ongoing coaching is essential and formalizing the decision-making process based on data and information. Shah, Horne and Capella stated that “many of the best data-driven cultures have formalized the decision-making process, setting up standard rules so that employees can get and correctly use the most appropriate data. Companies should make performance metrics transparent and embed the in job goals. They should also make sure that compensation systems reward dialogue and dissent. Great decisions often need diverse contributions, challenges, and second-guessing”.
Tiffany and BCBSNC are the great example of companies who have shown growing awareness of the pay-offs from Big Data and data literacy.
Is your organization underinvested in understanding the information and maximize Big Data ROI?
Source: Harvard Business Review April 2012,
Article: Good Data Won’t Guarantee Good Decisions
Writers: Shvetank Shah who leads the information technology practice at Corporate Executive Board, Andrew Horne and Jaime Capella, who anre managing directors at Corporate Executive Board