Understand Prescriptive Analytics in 20 Minutes

Summary

In this webinar, Laura Van Dijken and John DeLong discuss the importance of prescriptive analytics, its value to businesses, and practical applications. John highlights the evolution from descriptive to prescriptive analytics, emphasizing the shift from data interpretation to actionable insights. He showcases how companies are leveraging optimization and predictive modeling to improve decision-making, increase efficiency, and drive business growth. The presentation also covers the increasing adoption of prescriptive analytics, its potential in various industries, and the challenges businesses face in becoming more agile and data-driven.

Takeaways

• 📚 Prescriptive analytics is a field that has gained significant interest and value for companies, with a forecasted growth from 10% to 35% by 2020.
• 🔍 The field of analytics has evolved from standard reporting to more advanced forms such as predictive modeling and optimization.
• 📈 Optimization is distinguished from other analytics by focusing on what could be the best outcome rather than just interpreting data.
• 🚀 Companies are moving towards using prescriptive analytics to gain a competitive edge, improve margins, and enhance customer satisfaction.
• 📈 Google Trends data shows an increasing interest in analytics, including prescriptive analytics, over time.
• 📊 The transition from descriptive to prescriptive analytics often starts with simple tools like Excel, but grows to more complex and integrated solutions.
• 💡 Prescriptive analytics allows for modeling the business as it is, providing flexibility and the ability to innovate beyond predefined processes.
• 🔄 Companies using prescriptive analytics can make decisions more frequently and with greater effectiveness, leading to improved performance.
• 📈 The application of prescriptive analytics is widespread, but notable in industries like sales, network optimization, oil and gas, and retail.
• 💼 Organizations are seeking agility and the ability to quickly test and implement new strategies, which prescriptive analytics can facilitate.
• 🔗 As companies adopt prescriptive analytics, they may need to reevaluate traditional business processes and roles to fully realize its benefits.

Q & A

What is the main focus of the webinar?

The main focus of the webinar is to provide an overview of prescriptive analytics, explain why companies find it valuable, and share examples of its application.

Who is the presenter of the webinar?

The presenter of the webinar is John DeLong, who has over two decades of experience in the prescriptive analytics space and works closely with research organizations like Gartner.

What is the significance of Tom Davenport's book 'Competing on Analytics' mentioned in the script?

Tom Davenport's book 'Competing on Analytics' is significant because it was one of the first books to connect the analytics side of business with the business side, emphasizing the importance of analytics leverage.

What does the analytics ladder mentioned in the script represent?

The analytics ladder represents the degree of intelligence and data utilization, starting from the basis of data to more advanced analytics like statistical analysis, forecasting, optimization, and ultimately prescriptive analytics.

How does optimization differ from the other forms of analytics mentioned in the script?

Optimization differs from other forms of analytics in that it focuses on recommending the best possible outcomes by modeling the business, rather than just analyzing data or predicting trends.

What is the forecasted growth of organizations using prescriptive analytics according to Gartner?

Gartner forecasts that the percentage of organizations using prescriptive analytics will grow from about 10% to 35% by 2020.

What does the script suggest as the starting point for businesses interested in prescriptive analytics?

The script suggests that businesses often start with tools like Excel for analytics, but as they understand the value, they look for solutions that can be configured to their business needs.

What is the importance of modeling in prescriptive analytics as discussed in the script?

Modeling is important in prescriptive analytics because it allows businesses to model their operations accurately, providing decision support tools that give answers based on the business model rather than general assumptions.

What are some common applications of prescriptive analytics mentioned in the script?

Some common applications of prescriptive analytics mentioned in the script include sales and operations planning, network optimization, and scheduling in industries like oil, gas, and chemicals.

How does the script describe the transition from traditional business planning to using prescriptive analytics?

The script describes the transition as moving from traditional tools like Excel to more advanced, configurable solutions, and eventually to embedding prescriptive analytics technologies that are not limited by specific business processes.

What challenges does the script identify with using spreadsheets for complex business planning?

The script identifies that spreadsheets become inadequate for complex situations and recurring planning issues, as they are limited in scalability, transferability, and the number of users that can interact with them.

Outlines

00:00

📚 Introduction to Prescriptive Analytics

Laura Van Dijken from AIMMS introduces the webinar on prescriptive analytics. She welcomes attendees and sets the stage for the discussion, highlighting the importance of understanding this analytical category. John DeLong, an expert with over two decades of experience, is introduced as the presenter. The talk begins with a reference to Tom Davenport's 2007 book, 'Competing on Analytics,' which emphasized the connection between analytics and business operations. The discussion then moves to the progression from traditional reporting to more advanced analytics like statistical analysis, forecasting, predictive modeling, and optimization. The aim is to provide insights into how businesses can leverage these tools to gain a competitive edge.

05:01

📈 The Evolution and Growth of Prescriptive Analytics

The script discusses the evolution of prescriptive analytics, noting the increased interest over time as evidenced by Google Trends data. It contrasts the growing interest with the temporary spikes in searches related to unrelated events like the Super Bowl. The discussion then shifts to the transition from using basic tools like Excel to more sophisticated solutions that offer configurability and scalability. The importance of flexibility in business modeling is emphasized, as is the need for solutions that can be easily adopted by end-users within an organization. The segment concludes with a look at market forecasts that predict significant growth in the adoption of prescriptive analytics by businesses, indicating its importance as a strategic tool.

10:05

🚀 Implementing Prescriptive Analytics for Business Agility

This section delves into how companies can start implementing prescriptive analytics, emphasizing the shift from using spreadsheets to more advanced modeling techniques. It discusses the benefits of using analytics for more frequent decision-making, leading to better business performance. The speaker shares insights from a study that shows companies applying advanced analytics outperform their peers. The discussion also touches on the challenges companies face when their existing solutions limit growth or agility. The importance of being able to quickly test and iterate on business strategies is highlighted, with a recommendation to read 'The Lean Startup' by Eric Ries for insights on fostering agility within organizations.

15:06

🔍 Next Steps in Adopting Prescriptive Analytics

The final paragraph focuses on the next steps organizations can take to adopt prescriptive analytics. It suggests evaluating the potential benefits and identifying areas where current processes may be limiting business potential. The speaker encourages attendees to consider how prescriptive analytics could address these limitations and improve decision-making. The webinar concludes with an invitation for further discussion and the offer of additional resources. The speaker's contact information is provided for follow-up questions, and attendees are informed that they will receive slides, video links, and additional reading material after the webinar.

Keywords

💡Prescriptive Analytics

Prescriptive analytics is a branch of advanced analytics that provides guidance on the best course of action. It uses various techniques like predictive modeling, statistical analysis, and machine learning to suggest the best possible outcome for a given situation. In the video, prescriptive analytics is discussed as a tool that helps businesses optimize their operations and decision-making processes. An example from the script mentions how companies find prescriptive analytics valuable for understanding what could happen and how to make better decisions.

💡Optimization

Optimization in the context of the video refers to the process of making the best or most effective use of resources to achieve the desired outcome. It is a key component of prescriptive analytics, where mathematical models are used to find the most efficient solution to a problem. The script refers to optimization as a practice where companies are very active, aiming to find the best possible outcomes for their operations.

💡Analytics Ladder

The Analytics Ladder, as mentioned in the script, is a model proposed by Tom Davenport that illustrates the progression of analytics maturity in an organization. It starts with basic reporting and moves up to predictive and prescriptive analytics. The ladder is used in the video to show the evolution of how companies use data and analytics to gain insights and make decisions.

💡Gartner

Gartner is a renowned research and advisory company that provides insights on various aspects of technology and business. In the video, Gartner is referenced as an organization that John DeLong, the presenter, works closely with, indicating the credibility and industry recognition of the topics discussed, such as prescriptive analytics.

💡Descriptive Analytics

Descriptive analytics is the first step in the Analytics Ladder and involves analyzing historical data to describe what has happened in the past. It provides businesses with insights into their data. The script differentiates descriptive analytics from prescriptive by highlighting that the former describes what happened, while the latter prescribes what to do.

💡Predictive Analytics

Predictive analytics uses historical data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes. It is positioned above descriptive analytics on the Analytics Ladder. The video mentions predictive analytics as a step towards understanding future trends and potential outcomes, which is essential for making informed decisions.

💡Business Agility

Business agility refers to an organization's ability to adapt quickly to changes in the business environment. In the video, business agility is discussed as a key benefit of adopting prescriptive analytics, as it allows companies to make decisions faster and more effectively, thus becoming more competitive.

💡Data-Driven Decision Making

Data-driven decision making is the process of using relevant data to guide business strategies and actions. The video emphasizes the importance of data-driven decision making in the context of prescriptive analytics, where companies use data to not only understand what has happened but also to predict and prescribe actions.

💡Excel

Excel is mentioned in the video as a common tool used for basic data analysis and planning. However, it is also noted that as businesses grow and become more complex, they often outgrow Excel's capabilities, necessitating more sophisticated tools and methods such as prescriptive analytics.

💡Supply Chain

The supply chain is the network of organizations, people, activities, information, and resources involved in moving a product or service from supplier to customer. The video discusses how prescriptive analytics can be applied in the supply chain to optimize various aspects such as demand forecasting, inventory management, and logistics.

💡Case Studies

Case studies are mentioned in the video as examples of how companies have successfully implemented prescriptive analytics. They provide real-world examples and demonstrate the practical application and benefits of prescriptive analytics in various industries.

Highlights

Introduction to prescriptive analytics and its value to companies.

John DeLong's introduction, his experience, and association with Gartner.

Importance of Tom Davenport's book 'Competing on Analytics'.

Analytics lever and its significance in connecting business analytics.

The evolution from traditional reporting to advanced analytics.

The role of optimization in prescriptive analytics.

The impact of the 2007 financial crisis on data analytics.

Gartner's perspective on the progression from descriptive to prescriptive analytics.

The forecasted growth of prescriptive analytics usage in organizations.

The increasing interest in prescriptive analytics as shown by Google Trends.

The transition from using Excel to more advanced tools for analytics.

The benefits of configurable solutions in prescriptive analytics.

The importance of modeling business accurately in prescriptive analytics.

How prescriptive analytics helps in making better business decisions.

The significance of agility in adopting prescriptive analytics.

Common applications of prescriptive analytics in sales, logistics, and oil & gas industries.

The need for organizations to become more agile to adopt prescriptive analytics.

Recommendations for books and resources to understand prescriptive analytics.

Encouragement for organizations to evaluate and adopt prescriptive analytics.

The Q&A session addressing common applications and the industries leading in prescriptive analytics.

Transcripts

good morning everyone thanks for joining us today 

my name is Laura Van Dijken with the AIMMS marketing team and I'm going to be your 

host during the webinar I'd like to welcome you to today's webcast 

understand prescriptive analytics and 20 minutes we're gonna provide an overview 

about this exciting category why companies find it valuable and share 

some examples with you it's my pleasure today to introduce our presenter her 

John DeLong her John has been working with leading companies partners and 

universities around the world he also works closely with research 

organizations like Gartner and has over two decades of experience in the 

prescriptive analytics space he also actively speaks and blogs on the topic 

okay I'd like to start with 2007 it's a book that came out by Tom Davenport 

competing at analytics I think it's a very important book for our field it 

doesn't talk about prescriptive analytics yet but it talks about 

analytics lever and some of you might be familiar with it and if not I would 

highly recommend you read this book I think it's one of the first books that 

really wanted to connect the analytics sides of the business analytics first 

with the business side with the business side and if you look at this ladder it's 

very interesting from Tom death what looked at the degree of intelligent and 

of data data it's the basis here and then you think about you know do 

standard report ad hoc reports up til it alerts you know just understand what's 

we they're looking at it's very traditional what it was in the past but 

if you want to start complete under date now you want to do more with today to 

get more insights you know you have to start to do actual analytics sets work 

on the day time and there you go and just in two ways of statistical analysis 

to understand why things are happening but to look at forecasting see if the 

trends continue maybe do predictive modeling see what will happen next 

and on top of there we have optimization what's the best thing that can happen 

let's feel that we are very active in as well and the interesting about these 

topics is that if you look at what happened in 2007 it was just before the 

crisis people already looked at ways to get more with their business get more in 

their business more advances with the data get more insights and if you look 

at the difference as well between optimization and the other three 

analytics ones be on a three hour focus on I have data what does the data 

tell me the optimization sight on the air in their head gives you recommended 

actually what's the best thing that can happen and dairy has you started 

modeling actually the business and it's something what we'll see about a little 

bit more as well not long thereafter two other books came out Tom Davenport built 

or wrote analytics network but also there's a great book from Steve Sasha 

hari optimization act and that one folks very much on the top of the letter and I 

think it's a great testament of showing some examples what worked and what 

didn't work and which companies even survived and which company didn't 

survive and again if you're isn't understanding what you could do it talks 

about different people you have to have in place the way you have to approach 

your business I think those are great books to read as well and then the back 

by the way I have some reference for you to read more about things but again I 

think this was the first part where we saw for ourselves as well as an 

organization AIMMS we've been in business since 89 we're certainly people in 

business understood that what mathematical statistical analysis 

forecasting could actually mean for the business side and it allowed us to even 

start kind of analytics ways and you saw people talking about it even 

organizations like informs create a business and Olympics conference and 

that was new for us and I think it was very important to to cross that bridge 

but however it was still very focused on the engineers the people who knew about 

analytics or knew about these type of engineering mathematical technologies 

they could start applying it in the business but that's of course not for 

all businesses and I think when garden started to pick it up then we it became 

much more prominent it was starting to be discussed as well as a management 

level or at sea level and garden what it also did I think was very nicely in this 

chart let's see here it started to layer it a little bit differently it looked at 

on the left side you have data the starting point that's what you have what 

you know what you think you know but on the right in its action as a business 

you want to create actions and of course if you do actually want to have the 

right action so you want to make decisions for that and what you see in 

the green coloring is the human input input the light green coloring 

and with descriptive diagnostic and predictive you need human input to 

interpret data you need to make some kind of assumptions or combine certain 

data trying to find certain correlations well if you get too prescriptive and 

optimization is a part of prescriptive you start to actually model your 

business and it becomes a decision support tool it gives you answers based 

on your business instead of you finding out what the answers could be by using 

mathematical algorithms combining certain correlations using predictive 

insights bring them all together and that will give you insight on what you 

could do and gardening just also released a forecast of this business and 

they see now that about 10 percent of the organization actually use procedure 

type of prescriptive analytics but they forecast to grow that up to 35% 2020 so 

definitely it's a hot topic it's an important topic and now when you see it 

all around the world you know you want to squeeze the last mile out of your 

business whether it's on margin you want to improve your customer levels there's 

open to things you want to do and that's where prescriptive comes in play but of 

course we can sail it so I thought let's look at some other data and this is very 

descriptive data of course I thought let's look at Google Trends first Giffen 

analytics what happened over time and what you see here the gross from 2002 11 

through 2017 now it's growing more people are looking at it more people are 

interested in it so that's definitely a great testament I think to what we see 

that it supports the analytics and prescriptive analytics wave it didn't 

start exactly with the book I think 2011 but it's there where we saw the first 

signal of using these terminology of course we also have to be realistic and 

we all know the Super Bowl is coming up and you can exactly when Super Bowl is 

coming up here right now and the people who are interested Super Bowl are not 

necessarily interested prescript oolitic so we still have a long ways to go but 

again here also data again tells you hey when is the Super Bowl by seeing the 

spikes you know what's really having an NFL I think that's so interesting if you 

look at data how can I use the data become more efficient 

so to do all this you know there's there's different ways to look at it and 

and what we see is a new way a new approach of working with the business 

where traditionally when people started off doing some prescriptive analytics or 

predictive and other things you know a lot of people start with of course Excel 

or next shell like a tool and I don't want to be exhaustive in 

tools we've just given as an example because Excel is so easy to use you can 

make very easy datasets in it and you can submit now some trends and all the 

stuff when people get some insights but it's very very personal it's limited a 

number of users you can't really transfer it to water so running a 

business on it is pretty scary but you know it's being done with lots and lots 

of sex Health Week next to each other so but what happened when people understand 

the value of it they say well I want to think like taking next step are their 

parties out there that give me certain solution that it just have to configure 

if they have the knowledge about my business and by configure I am will be 

faster I believe faster than deploying it I can ease your support my teams I 

have very regularly used I'll make sure it's stable all that stuff and you know 

examples like Lamas often SFA APO or are great examples for that they already 

have big solution if you control of it you configure it and then it becomes 

right for your business that's all great of course but it's still limited its 

limited to the scope of what the solution is offering and if you didn't 

go all the way to the right you know we're we're really focusing on is you're 

making sure that if you want to embed these type of technologies you should 

not be limited by the specific way of doing your business you should not and 

some people call it set afire yourself if you don't adhere to the severals 

it's gonna be hard to put your business in there well if you want to 

differentiate yourself and become better or become more innovative you want to 

have also the flexibility in that and modeling allows you to do that it allows 

you to model it as your business is but of course you also have to have the 

other side it's not just a modeling and the application that it's also ability 

to really put it in the hand at the end users make it very easy turns fertile 

into the organization and there because if it's in the organization that's where 

you really get the value and that's in the end why we do it 

so in fact if you look at that it's if you start thinking about about modeling 

and optimization to prescriptive analytics side 

it doesn't have to be that hard to get started you know because as a business 

owner you typically have an object you want to achieve something it could be a 

cost minimization of your marketing budget it could be a manufacturing 

optimization cost optimization there it could be sourcing optimization how do I 

manage my contracts in the best possible way all these type of things trying to 

put optimization these types of things of course are all objective you you're 

after and and when you go after you want to make decision so what do I have to do 

how many how much should i transport how much should I produce I'm gonna start 

levels about half how should i pry certain things all these things are 

decisions that are flexible you can play with them to advance your business to 

increase your March to become more efficient but of course you also have 

your restrictions we're sticking to be physical but it could be strategic 

physical as you know a location has a certain storage facility it can only 

hold so much of a certain product they're only roads going from A to B and 

maybe enough from ABCs you have to go through a all these type of things are 

restriction you have to adhere into a model but it also be strategic for 

example in the sourcing oh you want to maybe source at least for two or three 

different suppliers your risk you minimize your risk and of course mother 

do you have wrinkles and your inputs could be all the systems you have here 

like your your transactional based systems you could be your Excel files or 

whatever but they could also be inputs that are maybe uncertain it could be 

like a demand forecast and you want to use that input as well and the end what 

you want to do if you have those four together and you put that into what we 

call a model you can start exporting combinations best possible combinations 

and you can understand the effect of certain decisions you can say well what 

if I would were to do this what if I were to supply so much to this 

location what would happen with my results these exploration of what-ifs 

gives you more understanding of the business gives you better decisions and 

a nice study and I'm trying to give you also some feedback out of the market and 

again those links are also in the back is Bane had a very nice study where they 

they looked at company supply chain and look at how they applied that font and 

let's build what happened if they were to do that first of all they looked at 

the company in that and then they realized that a lot of this company said 

well you know our serpentine is not so good in fact we think we're worse or 

maybe equal then our competitors or our peers whatever you would call them which 

of course this is quite a statement and means you want to become better and when 

they started applying analytics and advanced analytics specifically so that 

advanced analytics is the predictive and the prescriptive part where you start to 

do more than just looking at the day that really used models and algorithms 

to find new ways of running your business they started to use the data 

more frequently and therefore make decisions more frequently and I think 

that's important you have to make decisions yeah you're gonna let 

decisions go and say well we'll live with it 

but if you can make that faster it will help you become better and then do it 

more five times more likely but it also become more effective and I think that's 

that's also very important in executing decisions because you have more 

background you have more insights you feel more comfortable you get more 

understanding of maybe the robustness of a certain decision and giving you the 

comfort ability you also give you more comfort ability to actually make a 

change and that's important you have to vouch that you know the ROI is right or 

you can really deliver your your customer all these type of things are 

happening and of course that automatically pans out into becoming 

high performance and that's what you see as well they become outperforms the ones 

that are actually doing that and I think going back to the book of Steve 

optimization as I think he has some great examples in there I definitely 

recommend you to read that so what do we see in our company base when do people 

start to to use prescriptive analytics and the very obvious one and it happens 

when many many times and I think also because a lot of companies still run a 

lot of things in spreadsheets is that people aren't and spreadsheet and they 

cannot handle it complex situations and the recurring planning issues I we've 

seen customers where they're happy by the end of the week they have a planning 

in an Excel spreadsheet by just making sure that everything is tech tech back 

and forth and everybody knows except what's going on 15 goals around it it's 

very very complicated and actually not still running after your business you've 

just tried to get a plan and share your plan or making it transferable to a next 

version it's going to be even harder if you could model that you can just pull 

data in it and show solution and suddenly you go much faster and become 

much much much much better in executing eCos it starts thinking differently 

about your business because think what why do you do the things instead of what 

do we have to do so an example here 10 hours now takes 5 seconds you know these 

are really situations that we see happening and that's that's quite 

amazing the other thing is you know you see people that are limited in their 

growth because solution they have it could be shared 

before certain solution that you might purchase for a certain problem which 

could be inventory optimization or network optimization or something else 

it doesn't doesn't really matter but typically these solutions are within a 

certain space if you go outside you have to ask for change request and it's not 

standard so maybe you don't get it so you have to just do it outside the 

solution and we see more and more integration where people say I want to 

have seals an operation file together or I want to add contract values to my 

operational decisions it's very much if you if you're not able to do that you 

know that's the way we will say well I want to break out the standard I want to 

invest and understand how I can become better at something morally completeness 

of my business and I thirdly and this is not exhaustive but I think these are 

three different very important points people also sometimes feel stuck there 

is a certain process in the organization big systems are in place if you want to 

add something new you have an idea it's gonna take you six 12 18 months to get 

that started because you need everybody on board IT needs to be on board it 

needs to be a certain process it has wonderful techniques all these type of 

things are there it's not very agile and if you're not agile you know it's gonna 

be very hard to be very quickly active on the business so what we see people 

doing as well specifically if the question comes out of the business how 

can I become more agile in very quickly build something we talked a little about 

that approach later on as well you want to do it quick easy fast and get testing 

and understand some with some experimentation what you could do and 

that's not necessarily something that is standard in the IT side so as I said it 

is or I didn't say it but what we do see is you know it's no longer business as 

usual it would be where you have the standard says in the big shizz that 

they're all great you need an system of record but we also see that customers 

need more agility and you know you don't want to plan everything out the 

landscape is beautiful there will be hills and in the landscape it you have 

to pass on you have to go over it or around it all these things will happen 

and behind it will be something else that you might not know but you know 

it's it's it's something that just one of those step by step are we very very 

much advocate that Lean Startup I think from Eric Ries is a great book to read 

about it as well how can you as an organization become agile start trying 

it out testing it maybe you know go different paths because you don't see 

value go in that path if you do see value 

I think if you can do that that's a great testament I think your 

organization wants to adopt new ways of advancing their business so I want to 

talk a little bit about a few next steps I think what is important if you listen 

to this and I know you know it's very very limited because we only do it in 20 

minutes but evaluated that risk it's analytic for your business looking at 

this we'll have some references there are some books think about that what 

could it mean for you you see some potential and where are you frustrated 

limited stuck or do you just want to do this good you know as well because it 

helps you understand how to drive people how to change the organization and and I 

think that's the last part are you willing to change and we've seen many 

many times that people see the problem but you need a pretty solid base to want 

to change because it will change some of the roles of how people are doing 

instead of making a plan as spreadsheet suddenly you get to plant in front of 

you so it brings you to a new wave of working the business but that's also an 

opportunity I think for many of the important needs to to give them new ways 

of making better decision I think everybody is benefited from that and 

anyway so if you want you can talk and do it internally but they also who are 

happy to talk to you about it so please do reach out my contact needs are at the 

end you can write us an email we're happy to talk and help them in that 

process with that I want to bring it back to you and Laura all right well 

thank you coach on now we come to the Q&A portion of the webinar so if you 

have a question just use the questions window and submit your question and you 

can do so in the control panel right now and we'll take as many questions as time 

allows here's a question for John what are the most common applications for 

prescriptive analytics and is there like a common one that some companies start 

with interesting question of course you try to somehow generalize it over the 

whole world that's always going to be tough but it was interesting to see last 

year we shot a lot of sales preparation planning applications in different 

industries where people said well I have my demand my demand forecasts are 

getting better they're even looking a little bit of it can I do some more 

optimization on that side be more predictable and use them to steer the 

operations become more volatile or the story become more robust on a volatile 

demand because that's that's a big challenge that's one of them of course 

and I think that's even in the last five years 

network optimization is always a big one always a lot of consultants logistical 

analyst engineers are doing that what to do with my mind my network you logistics 

area those are two ones and what I also see a lot in the oil gas chemical 

industry there's a lot of optimization there on the scheduling world how do i 

schedule my refineries how do I ever show an example of the barge getting 

these type of things very very important and of course you're sorry there are - 

so there are many it's hard to choose just to give you some examples I think 

the retail space is always also very much picking up with the marketing side 

promotional side pricing side definitely and of course to have a large supply 

chain how to manage that and then if we have new ways to make money how can they 

take the next step Amazon is on their till so what do you 

do so would you say that those are the industries that are leading the pack the 

ones that you mentioned III think they're yeah I think they're definitely 

leading the pack so it's a hard thing to say but I think they're definitely very 

capable of doing these things and and willing to do these things and I think 

that's if they're building up these headphones and little put in the company 

are there making relationship with very good consulting companies that can help 

them do that all right thank you I just wanted to thank everyone for joining us 

today we hope that you enjoyed the information presented and a big thank 

you to John for the webcast again just to repeat we're going to be sending out 

the slides and a link to the video within the next few days so be on the 

lookout for that email and in the slides will include a list of resources if 

you'd like to learn more about the topic and if you actually go to the panel 

right now in the handouts there's a brochure that talks about prescriptive 

analytics and it actually has two short case studies that you can learn more 

about how prescriptive analytics is being used of course we have many more 

case studies and some customer stories on our website if you want to do a 

further deep dive below on the screen you'll also see a fair johns email so if 

you want to send him a question after the webinar please feel free to 

so and reach out to him directly well also in the pack that you'll be getting 

you'll see that there's a list of just some articles for you to read and refer 

to after the webinar as well if you want to learn more about it